Hire Data Engineers
in India
Senior data engineers ready in 48 hours. Build reliable ETL pipelines, real-time streaming with Kafka, and scalable data warehouses on Snowflake and BigQuery — at 60% less than local rates.
What Our Data Engineers Build for You
The data infrastructure that powers analytics, ML, and reporting
ETL / ELT Pipelines
Design and build data pipelines that extract from source systems, transform for analytics, and load reliably into your warehouse — with monitoring, alerting, and backfill support.
Data Warehouse Design
Architect Snowflake, BigQuery, or Redshift data warehouses — dimensional modelling, partitioning strategies, cost optimisation, and query performance tuning.
Real-Time Streaming
Build Kafka, Kinesis, or Pub/Sub streaming pipelines for real-time analytics, event processing, and live operational dashboards.
dbt Transformation Layer
Write version-controlled, tested SQL transformation models in dbt — building clean, well-documented data layers for analytics and ML teams.
Data Lake Architecture
Design S3, GCS, or Azure Data Lake Storage architectures with Delta Lake or Apache Iceberg for reliable, time-travel-capable data lakes.
Pipeline Orchestration
Set up Airflow, Prefect, or Dagster DAGs for reliable, observable, retryable data pipeline orchestration.
Data Quality Framework
Implement Great Expectations, dbt tests, or Monte Carlo for automated data quality checks that catch issues before they reach stakeholders.
Cloud Data Integration
Integrate SaaS data sources via Fivetran, Airbyte, or Stitch into your warehouse — CRM, billing, marketing, and product analytics.
Data Governance
Implement column-level security, PII masking, lineage tracking, and data catalogues for compliant, well-governed data platforms.
Data Engineering Tools & Technologies We Cover
Why Hire Data Engineers Through TechTeamsOnline?
End-to-End Data Stack
Our data engineers handle the full stack — ingestion, transformation, warehousing, orchestration, and quality monitoring.
48-Hour Matching
Receive 2–3 pre-vetted data engineer profiles in 48 hours.
7-Day Risk-Free Trial
Work with your data engineer for a full week. Not the right fit? Pay nothing.
60% Cost Savings
Hire senior data engineers at $2,000–$5,000/month versus $130,000–$200,000/year locally.
Cloud-Agnostic
Our engineers work across AWS, GCP, and Azure data stacks — Snowflake, BigQuery, Redshift, and beyond.
Free Replacement Guarantee
If your engineer underperforms or leaves, we replace within 7 days at no cost.
How We Vet Data Engineers
Experience Screen
We review data pipeline designs, warehousing projects, and data platform work delivered.
Technical Assessment
Write a dbt model, design a Kafka consumer, and optimise a Snowflake query.
Data Architecture Interview
Design an end-to-end data platform: ingestion, transformation, serving, and quality.
Communication Fit
English proficiency and ability to collaborate with data science and analytics teams.
What Clients Say About Our Data Engineers
"Our data engineer rebuilt our Airflow pipelines and our data is now always fresh, tested, and reliable. The analytics team loves it."
"The Snowflake migration our engineer led reduced our query costs by 50% and query times from minutes to seconds. Exceptional work."
"Real-time Kafka pipelines built by our data engineer now power our operational dashboard. We can see what's happening in our business live."
Frequently Asked Questions
What does a data engineer do?
A data engineer builds the infrastructure for data — designing and maintaining ETL/ELT pipelines, data warehouses, data lakes, and streaming platforms to ensure clean, reliable data flows to analytics and ML teams.
What is the difference between a data engineer and a data scientist?
A data engineer builds the plumbing — pipelines, storage, and infrastructure. A data scientist uses that infrastructure to extract insights and build models. We often recommend both in tandem for a complete data team.
Can your data engineers build real-time streaming pipelines?
Yes. Our engineers design real-time streaming architectures using Apache Kafka, Kafka Streams, AWS Kinesis, or Spark Structured Streaming.
What data warehouses do your engineers work with?
Snowflake, BigQuery, Redshift, and Azure Synapse. They design schema, implement partitioning strategies, and optimise query performance and cost.
Do your data engineers use dbt?
Yes. dbt is a core skill. Our engineers write SQL transformations as version-controlled code with tests, documentation, and modular data models.
Can they build pipelines on AWS Glue, Azure Data Factory, or GCP Dataflow?
Yes. Our engineers are proficient in cloud-native ETL services across AWS, Azure, and GCP — choosing the right tool for your stack.
Ready to Hire a Senior Data Engineer?
Get 2–3 pre-vetted data engineer profiles in 48 hours. Start with a 7-day risk-free trial.