Data Engineering Services
Reliable data pipelines, scalable warehouses, and real-time analytics that turn raw data into business decisions.
10M+
Events processed daily
Data is only valuable when it's reliable, timely, and accessible to the people who need it. Techgynt's data engineering practice builds the infrastructure that gets data from your source systems into the hands of analysts and decision-makers — cleanly, quickly, and consistently. We process over 10 million events per day across client deployments and have yet to miss an SLA.
We build ETL and ELT pipelines that handle the full complexity of real-world data: schema changes, late-arriving records, duplicates, API rate limits, and source system downtime. Our pipelines are designed to fail gracefully — with alerting, automatic retries, and data quality checks at every stage — rather than silently delivering wrong numbers.
Our warehouse architecture practice covers Snowflake, BigQuery, and Redshift. We design schemas optimised for analytical query patterns (not transactional ones), implement incremental loading strategies to keep costs manageable at scale, and build dbt transformation layers that are version-controlled, tested, and documented. Your analysts can trust the numbers because we've built the tests that prove them.
Real-time analytics is increasingly a competitive requirement. We build streaming pipelines using Apache Kafka and Flink that let you act on events as they happen — whether that's fraud detection, live inventory updates, or real-time customer personalisation. Our Gujarat-based data engineering team has delivered real-time systems that process millions of events per second with sub-second latency.
What's Included
Everything you need to go from idea to production — handled by one team.
ETL / ELT Pipeline Development
Reliable ingestion, transformation, and loading pipelines with data quality checks, alerting, and automatic recovery built in.
Data Warehouse Design
Snowflake, BigQuery, and Redshift architectures designed for analytical performance, with dbt transformation layers and full test coverage.
Real-Time Streaming Pipelines
Apache Kafka and Flink pipelines that process millions of events per second with sub-second latency for live dashboards and event-driven automation.
Analytics Dashboards & BI
Self-service BI dashboards connected to your warehouse — built in Metabase, Grafana, or custom React — so every team can find their own answers.
Technologies & Tools
Frequently Asked Questions
Common questions about our data engineering services.
ETL (Extract, Transform, Load) transforms data before loading it into the warehouse — common in older on-premise setups. ELT (Extract, Load, Transform) loads raw data first, then transforms it inside the warehouse using tools like dbt. ELT is generally preferred today because cloud warehouses are powerful enough to handle transformations at scale, and keeping raw data gives you flexibility to rebuild transformations without re-ingesting.
Let's Work Together
Ready to get started?
Tell us what you're building. We'll get back within 24 hours with a clear technical plan.