Why Choose Ratech
We deliver production-grade data infrastructure that powers decisions and drives growth, not fragile scripts that break every week
7+
years of data engineering experience across high-volume production systems
3x
faster delivery than traditional development agencies
End-to-end
ownership — from data analysis to production deployment
Long-term
we focus on partnership approach to improve continuously
Cost-Effective
40% lower costs vs building in-house teams
ROI in 1-3 Months
from faster decisions and reduced manual work
Data Problems We Solve for Growing Businesses
Data lives in 15 different places and nobody can find anything
Centralized data warehouse that consolidates data from all systems into one place. Everyone accesses the same reliable source instead of hunting through databases, and asking IT for exports.
Reports take days to create and are outdated before you finish
Automated data pipelines that keep dashboards updated in real-time. Executives see current numbers instantly, not last week's data in manual reports built over days of Excel hell.
Half your team's time is wasted cleaning and preparing data
ETL pipelines that automatically clean, transform, and structure data. Analysts spend time finding insights instead of fixing data quality issues and reconciling conflicting numbers.
You're making million-dollar decisions based on gut feel
Reliable data infrastructure that gives you confidence in numbers. Make strategic decisions backed by accurate, real-time data instead of assumptions and outdated information.
Data quality is a mystery until reports show wrong numbers
Data quality monitoring that catches errors before they reach dashboards. Automated validation alerts you when numbers don't make sense instead of discovering issues in quarterly reviews.
Scaling is impossible because your systems can't handle growth
Scalable data architecture built on modern cloud infrastructure. Handle 10x data volume without rebuilding systems or hiring armies of data engineers.
Data Engineering Services
From data warehouses to real-time pipelines — infrastructure that makes your data work for you
Let’s talkData Warehouse Design & Implementation
Build centralized data warehouse optimized for business intelligence. Consolidate data from all sources into single source of truth with proper structure, governance, and access controls.
ETL/ELT Pipeline Development
Automate data extraction, transformation, and loading from any source. Create reliable pipelines that run on schedule, handle errors gracefully, and keep your warehouse current without manual intervention.
Real-Time Data Streaming
Process data as it happens for up-to-the-second insights. Build streaming pipelines for real-time dashboards, instant alerts, and applications that need current data, not yesterday's batch.
Data Quality & Governance
Implement validation rules, monitoring, and alerts that ensure data accuracy. Establish governance policies for access control, data lineage, and compliance with regulations.
Cloud Data Infrastructure
Migrate on-premise systems to scalable cloud platforms (AWS, Azure, GCP). Reduce costs by 40% while improving performance, reliability, and ability to handle growth.
Industries We Serve
Building data infrastructure that scales with your industry's unique challenges
Marketing
Recruitment & HR
E-commerce
SaaS
Real Estate
Construction
Banking & Finance
Healthcare
Logistics
Education
Travel & Hospitality
Web Agencies
See all industries AI solutions
Marketing Data Solutions
Stop arguing about which numbers are right
Single data warehouse combines ad platforms, CRM, analytics, and attribution into one source of truth. Everyone references same numbers in meetings, no more conflicting reports.
See campaign ROI in real-time, not next week
Automated pipelines pull spend and conversion data hourly. Know which campaigns are working while they're running, not after budget is spent.
Track customer journey without manual stitching
Data pipelines connect every touchpoint - website visits, email opens, ad clicks, purchases. See complete customer path automatically without analyst detective work.
Scale marketing analytics without hiring data team
Self-service dashboards let marketers explore data independently. IT builds infrastructure once, marketing generates own insights forever.
Recruitment & HR Data Solutions
Actually know your hiring funnel numbers
Warehouse consolidates ATS, job boards, and interview scheduling data. Track conversion rates from application to hire by source, role, and recruiter automatically.
Stop manually tracking employee data in spreadsheets
Central HR data warehouse combines payroll, performance, benefits, and attendance. Generate compliance reports in minutes, not days of data collection.
Identify retention patterns before people leave
Pipeline brings together compensation, tenure, performance, and survey data. Spot trends in departures before mass exodus happens.
Measure recruiter and hiring manager performance
Automated dashboards show time-to-fill, offer acceptance rates, and new hire performance by recruiter and department - no more manual tracking.
E-commerce Data Solutions
Know what's selling across all channels instantly
Real-time pipelines sync sales from website, marketplaces, retail locations into central warehouse. See inventory and revenue across business in single dashboard.
Stop inventory surprises that cost sales
Data warehouse tracks inventory by SKU and location with hourly updates. Avoid stockouts of hot items and overstock of slow movers.
Understand customer behavior across platforms
Pipelines connect online browsing, in-store purchases, app usage, and support tickets. See complete picture of customer engagement across touchpoints.
Measure true profitability by product and channel
Warehouse combines revenue, COGS, shipping, returns, and marketing spend. Know which products and channels actually make money after all costs.
SaaS Data Solutions
Track product metrics without engineering backlog
Data warehouse consolidates application events, usage logs, and subscription data. Product managers query metrics themselves without bothering engineers for exports.
See cohort retention and expansion revenue
Automated pipelines calculate cohort behavior, MRR movements, and expansion patterns. Track SaaS metrics that matter without manual spreadsheet updates.
Monitor application health in real-time
Streaming pipelines surface performance issues, error rates, and user experience problems. Catch issues before they impact customers or churn.
Measure feature adoption immediately after launch
Event pipelines track feature usage from day one. Know if new features drive engagement or get ignored - make product decisions on data, not opinions.
Real Estate Data Solutions
Stop manually compiling property data
Warehouse aggregates MLS listings, property records, market data, and your pipeline. Generate market reports in minutes that used to take days.
Track agent performance without spreadsheets
Pipelines combine showings, offers, closings, and client feedback. See which agents perform, which marketing works, all in real-time dashboard.
Understand market trends before competitors
Automated data collection and analysis of comparable sales, days on market, and price changes. Spot trends early to advise clients better.
Measure marketing ROI by property and channel
Warehouse tracks which listing sites, ads, and open houses drive actual buyers. Allocate marketing budget based on what works, not guesses.
Construction Data Solutions
Actually know project costs in real-time
Data pipelines pull from accounting, purchase orders, time tracking, and change orders. See true project costs daily, not when accountant finishes quarterly reconciliation.
Track subcontractor performance with data
Warehouse combines project schedules, quality issues, and payment history. Know which subs deliver on time and budget before awarding next contract.
Forecast material needs based on pipeline
Pipelines analyze bid pipeline, current projects, and historical usage to predict material needs. Buy in bulk when prices are low instead of panic-buying.
Stop chasing paperwork for compliance reporting
Automated data collection from project management tools generates safety reports, certified payroll, and regulatory filings. Compliance becomes button-click, not week-long project.
Banking & Finance Data Solutions
Consolidate data from legacy systems
Pipelines extract from mainframes, core banking systems, and modern apps into unified warehouse. Finally see complete customer view without system constraints.
Real-time fraud monitoring across channels
Streaming pipelines process transactions instantly from all channels. Detect fraud patterns in milliseconds, not batch processing overnight.
Regulatory reporting without manual data gathering
Warehouse maintains transaction history, customer data, and risk metrics in compliant format. Generate required reports on schedule automatically.
Customer 360 view for better service
Data warehouse combines transactions, interactions, products, and external data. Front-line staff see complete customer picture to provide informed service.
Healthcare Data Solutions
Aggregate patient data across systems
Warehouse consolidates EMR, billing, labs, imaging, and scheduling into unified patient record. Providers see complete history without clicking through five systems.
Track operational efficiency in real-time
Pipelines pull appointment volumes, wait times, procedure times, and resource utilization. Optimize operations based on actual data, not staff estimates.
Measure provider performance and outcomes
Data warehouse combines patient satisfaction, treatment outcomes, and efficiency metrics. Identify top performers and improvement opportunities objectively.
Simplify quality measure reporting
Automated pipelines calculate CMS quality metrics, HEDIS measures, and certification requirements. Submit reports on deadline without manual chart reviews.
Logistics Data Solutions
Real-time visibility across entire operation
Streaming pipelines track vehicles, shipments, and warehouse activities. See where everything is and how operations perform at any moment.
Measure carrier performance across dimensions
Warehouse combines on-time delivery, damage rates, costs, and customer satisfaction. Make carrier decisions on complete performance picture, not just price.
Optimize routes with historical performance data
Pipelines collect actual route times, traffic patterns, and delivery success. Plan better routes based on reality, not theoretical drive times.
Predict capacity needs before bottlenecks
Data warehouse analyzes volume trends, seasonality, and growth patterns. Know when to add trucks, staff, and warehouse space before hitting limits.
Education Data Solutions
Consolidate student data from disconnected systems
Warehouse combines SIS, LMS, admissions, financial aid, and library systems. See complete student journey without toggling between databases.
Track student success metrics that matter
Pipelines calculate retention, graduation rates, course performance by demographics and programs. Identify at-risk students and successful interventions with data.
Optimize course scheduling and resource allocation
Data analysis of enrollment patterns, room utilization, and faculty load. Schedule efficiently based on actual demand, not last year's guesses.
Measure program ROI and outcomes
Warehouse connects enrollment costs, completion rates, time-to-degree, and employment outcomes. Know which programs deliver value and which need improvement.
Travel & Hospitality Data Solutions
Unify data from booking, PMS, and POS systems
Warehouse consolidates reservation, guest preference, and spending data. Deliver personalized service based on complete guest profile, not siloed systems.
Real-time revenue management decisions
Streaming pipelines feed booking pace, competitor pricing, and event data. Adjust pricing dynamically based on current market, not yesterday's snapshot.
Track guest satisfaction across touchpoints
Pipelines aggregate reviews, surveys, complaints, and repeat bookings. Identify service issues before they trend on social media.
Measure marketing effectiveness by guest segment
Warehouse connects marketing campaigns to actual bookings and lifetime value. Invest in channels that bring high-value guests, not just clicks.
Web Agencies Data Solutions
Client reporting without manual data collection
Pipelines pull from analytics, ad platforms, SEO tools, and CRMs automatically. Generate client reports in minutes, not hours of copying numbers.
Track project profitability in real-time
Warehouse combines time tracking, expenses, and billing. Know which projects and clients are profitable before you're underwater.
Measure team utilization and capacity
Data pipelines track billable hours, project load, and bench time. Make hiring and staffing decisions on actual utilization data.
Forecast revenue with accurate pipeline data
Warehouse analyzes sales pipeline, project timelines, and historical close rates. Predict cash flow and revenue with confidence instead of hoping.
Service Options
Start with data assessment to identify quick wins, or jump into full infrastructure build
Consulting
Not sure what data infrastructure you need? Start with a low-risk assessment where we audit your current data landscape, identify bottlenecks, and create a roadmap with clear ROI projections.
Book 30 min call
End-to-end Engineering
Entrust the complete data infrastructure to us: warehouse design, pipeline development, quality monitoring, cloud migration, BI integration, and ongoing maintenance and optimization.
Contact UsRatech Expertise and Benefits of Data Engineering services
Data Science Expertise
Our engineers have over 7 years of experience in AI/ML and Data science, delivering E-commerce, Fintech, SaaS solutions. Proficient in data engineering, programming languages and skilled project management we ensure top-quality.
Lean Implementation
Through proven frameworks and modern tools, we deliver working data warehouse in 6-8 weeks, not 6 months. You see value quickly with incremental releases and continuous improvements.
Secure and Compliant
Ratech follows strict compliance with GDPR, HIPAA, and ISO. Every project starts with NDA and data protection protocols. Your product remains legally safe, transparent, and fully aligned with international data standards We handle security from day one.
Always-On Maintenance
We continuously adapting to new data and business changes. Your system stays accurate, secure, and profitable 24/7. We provide proactive monitoring, and propose improvements.
All-in-One
We handle everything — strategy, development, integration, and long-term support. One accountable partner driving your success from concept to scale. No coordination between multiple vendors, no gaps in responsibility.
Cost Efficiency
Eliminate manual data work, reduce report-building time by 80%, and make faster decisions. Typical ROI of 5-10x within first year through time savings and better business outcomes.
Use Cases and Solutions you get with Ratech
From data lakes to real-time streams — infrastructure capabilities that make data accessible and actionable
Centralized data warehouse
Single source of truth that consolidates data from all business systems. Everyone accesses same reliable data for analysis, reporting, and decision-making. End spreadsheet chaos and conflicting numbers.
Automated ETL pipelines
Extract data from any source, transform to consistent format, load to warehouse on schedule. No more manual exports, cleaning in Excel, or stale data. Dashboards update automatically.
Real-time data streaming
Process data as events happen for up-to-the-second visibility. Power real-time dashboards, instant alerts, and applications that need current information, not batch updates from last night.
Data lake for unstructured data
Store logs, documents, images, and other unstructured data cost-effectively. Make all data available for future analysis without knowing exact use case upfront.
BI tool integration
Connect warehouse to Tableau, Power BI, Looker, or other BI platforms. Enable self-service analytics where teams build own reports and dashboards without IT creating each one.
Data quality monitoring
Automated validation checks, anomaly detection, and alerts when data looks wrong. Catch issues in pipelines before bad data reaches decision-makers and damages trust.
Alex Zhytnykov
Data Engineering Expert at Ratech
Get a free consultation from our expert to transform your data chaos into reliable infrastructure
Get a free consultationStep-by-step process: Ratech Data Engineering
1
Data Landscape Assessment
Current state analysis
System inventory: Catalog all data sources - databases, SaaS tools, files, APIs, legacy systems. Document what data exists where.
Data flow mapping: Understand how data moves through organization currently. Identify manual processes, spreadsheet gymnastics, and integration points.
Pain point identification: Interview stakeholders to understand data struggles - access issues, quality problems, reporting delays, conflicting numbers.
Use case prioritization: Define what business questions need answering and which use cases deliver highest ROI from better data infrastructure.
Infrastructure planning
Architecture design: Design target data architecture - warehouse structure, pipeline framework, cloud platform selection based on requirements and budget..
Technology selection: Choose optimal tools and platforms for your needs - cost-effective and proven solutions, not experimental tech.
Migration strategy: Plan how to move from current state to target with minimal business disruption. Phase implementation for early wins.
Success metrics: Define KPIs for infrastructure success - data freshness, query performance, user adoption, time savings, cost reduction.
2
Data Warehouse Design
Schema design
Business requirements: Translate business questions into data model requirements. Ensure warehouse supports analysis teams actually need.
Dimensional modeling: Design fact and dimension tables optimized for business intelligence queries. Balance query performance with maintenance simplicity.
Historical tracking: Implement slowly changing dimensions to track how data changes over time. Enable trend analysis and point-in-time reporting.
Security and access: Design role-based access controls. Ensure sensitive data protected while enabling appropriate access.
Infrastructure setup
Cloud environment: Provision warehouse on chosen platform (Snowflake, Redshift, BigQuery) with proper sizing for current and projected needs.
Network configuration: Set up secure connections between data sources and warehouse. Configure VPNs, private links, and firewall rules.
Development environment: Create separate dev, test, and production environments. Enable safe development and testing without impacting live data.
Backup and recovery: Implement automated backups and disaster recovery procedures. Ensure business continuity if issues occur.
3
Pipeline Development
Data extraction
Source connections: Build connectors to all data sources using APIs, database links, or file transfers. Handle authentication and rate limits.
Incremental loading: Design pipelines to extract only new/changed data, not full data dumps every time. Reduce processing time and costs.
Error handling: Implement retry logic and alerting for connection failures. Pipelines recover from transient issues automatically.
Schedule optimization: Set extraction schedules based on business needs - some data needs real-time updates, other data fine with daily batch.
Data transformation
Cleaning and validation: Remove duplicates, fix formatting issues, validate data meets business rules. Ensure quality before loading to warehouse.
Data enrichment: Enhance data with lookups, calculations, and derived metrics. Transform raw data into business-ready information.
Standardization: Convert data from different sources to consistent formats, units, and naming conventions. Enable cross-system analysis.
Aggregation: Pre-calculate common metrics and summaries. Improve query performance by avoiding repeated calculations.
4
Quality & Testing
Data quality
Validation rules: Implement checks for completeness, accuracy, consistency, and timeliness. Alert when data violates expectations.
Anomaly detection: Monitor for unusual patterns - sudden spikes, drops, or changes that might indicate data issues.
Reconciliation: Compare source system totals with warehouse totals to ensure nothing lost in translation. Verify critical numbers match.
Data profiling: Analyze data distributions, null rates, and value patterns to understand quality and identify improvement opportunities.
Pipeline testing
Unit testing: Verify each transformation logic works correctly on sample data before deploying to production.
Integration testing: Test complete end-to-end pipelines with realistic data volumes to ensure performance meets requirements.
Failure scenario testing: Verify pipelines handle errors gracefully - missing source data, malformed records, API outages.
Performance testing: Ensure pipelines complete within required timeframes even as data volumes grow.
5
Deployment & Enablement
Production launch
Phased rollout: Start with single data source and use case. Validate before expanding to additional sources and users.
Monitoring setup: Implement dashboards tracking pipeline execution, data freshness, query performance, and user activity.
Documentation: Provide data dictionary, ERD diagrams, pipeline documentation, and operational procedures.
Cutover planning: Coordinate transition from old reporting systems to new warehouse. Parallel run to validate accuracy.
User enablement
Analyst training: Teach data team how to query warehouse, build reports, and understand data structure. Enable self-service analytics.
BI tool integration: Connect Power BI, Tableau, or other tools to warehouse. Build starter dashboards demonstrating capabilities.
Best practices: Establish guidelines for query optimization, dashboard design, and data governance.
Support process: Create procedures for requesting new data sources, reporting issues, and getting help with analysis.
Looking for something quicker and easier? We’ve got you covered!
Let’s talkEngagement models
Select the collaboration format that aligns with your data infrastructure needs
Dedicated Team
A complete data engineering team — including data architects, pipeline engineers, and analytics engineers — working exclusively on your data infrastructure from design to deployment and continuous optimization.
Time & Materials
Pay only for actual development time and resources used, with complete flexibility to adjust data infrastructure scope, add new sources, and pivot priorities as your analytics needs evolve.
Augmented Team
Strengthen your existing data team with our data engineering specialists who integrate seamlessly into your workflows, filling technical gaps and accelerating your infrastructure initiatives.
Ratech — Your Partner in Growth & Data Engineering
80%
reduction in time spent on manual data tasks
99.9%
uptime for production data pipelines
10x
faster report generation with automated pipelines
24/7
automated operations without human intervention
Technology stack
Ratech uses modern cloud platforms and proven tools to build scalable, reliable data infrastructure
Algorithms and Approaches
ETL/ELT Tools
Libraries & Tools
Databases & Data Storage
Data Integration
Data Quality
BI & Visualization
Languages
Data Engineering Frameworks
Data Engineering Tools
Environment & Packaging
DataOps & Deployment
Monitoring & Observability
Algorithms and Approaches
NLP (Text Classification, Sentiment Analysis, Text Summarization, Text Generation, etc.)
Computer Vision (Image Classification, Image Segmentation, Object Detection, OCR, etc.)
Autoencoders
Transformers
Neural Networks
Deep Learning
Probabilistic ML
Unsupervised Learning (Clustering, Outlier Detection, etc.)
Semi-Supervised Learning
Supervised Learning (Classification, Regression, etc.)
ETL/ELT Tools
Apache Airflow
dbt (data build tool)
Fivetran
Stitch
Talend
Pentaho
Libraries & Tools
Pandas
NumPy
Polars
Dask
Matplotlib
Seaborn
Statsmodels
Prophet
ARIMA/SARIMA
Databases & Cloud Data Warehouses
Snowflake
Redshift
BigQuery
Synapse
Databricks
Kafka
Airflow
TimescaleDB
PostgreSQL
MySQL
SQLite
MongoDB
Redis
Cassandra
DynamoDB
Vector DB: Pinecone, Weavite, Qdrant
Data Integration
Kafka
Spark
Glue
Data Factory
Dataflow
Data Quality
Great Expectations
deequ
soda-core
Monte Carlo
Datafold
BI & Visualization
Tableau
Power BI
Looker
Metabase
Superset
Languages
Python
JavaScript (Node.JS)
SQL
C++
Data Engineering Frameworks
Scikit-learn
SciPy
Tensorflow & Keras
PyTorch
PyTorch Lightning
XGBoost/LightGBM
Transformers
SentenceTransformers
Data Engineering Tools
PyCharm
DataSpell
Jupyter Lab/Notebook
Google Colab
AWS Sagemaker
Environment & Packaging
Docker
Conda
Poetry/pip
DVC (Data Version Control)
Git
DataOps & Deployment
FastAPI
Streamlit/Gradio
Docker
CUDA
AWS
AWS SageMaker Pipelines
Azure
Kuberflow
Weight & Biases
Neptune.ai
MLflow
DVC
Supervisely
GitHub Actions
CI/CD
Sentry
Monitoring & Observability
Datadog
Prometheus
Grafana
New Relic
PagerDuty
FAQ
What are data engineering services?
Data engineering services involve building the data infrastructure and tools to ingest, clean, process, and serve raw data from diverse sources. These comprehensive services enable data-driven decision making, support data scientists and analysts, and ensure data quality and data governance throughout the entire data lifecycle.
How do you quantify business value from your data science projects?
We define clear KPIs before the project begins and continuously monitor performance after deployment to measure impact and ensure value delivery.
How do you ensure data quality and reliability in your models?
Our data science experts perform comprehensive data cleansing, validation, and preprocessing. We also implement automated monitoring systems to maintain model accuracy and data integrity over time.
Can your solutions integrate with our existing systems (EHR, core banking systems, CRMs, etc.)?
Yes. We design and develop solutions that seamlessly integrate with your existing infrastructure and software platforms to provide smooth data flow and interoperability.
How do you handle model retraining and updates over time?
We provide ongoing monitoring to track model performance and regularly retrain or update models to maintain accuracy, relevance, and alignment with evolving business needs.
What if our data is messy and incomplete?
That's normal - most data is messy. We build data cleaning and validation into pipelines to handle real-world data quality issues. Part of our job is making imperfect data usable for business decisions.
Can you work with our legacy systems?
Yes. We have extensive experience integrating legacy databases, mainframes, and systems without modern APIs. We use database connections, file exports, or custom connectors to extract data from any system.
How much will cloud data infrastructure cost?
Costs vary based on your data, project complexity, and scope. We offer a free consultation to help identify the best solution tailored to your business needs and budget.
How do you manage sensitive data, and what security protocols do you follow?
Security is built into architecture from day one. We implement encryption, access controls, audit logging, and compliance features required for GDPR, HIPAA, SOC2, or industry-specific regulations.