Hire a Data Engineer

Get a pre-vetted data engineer for scalable ETL pipelines, data warehouses, and real-time streaming architectures — AI-managed delivery.

Role: Data Engineer (Data)

Data engineers design and build the infrastructure that moves, transforms, and stores data at scale. Our vetted data engineering talent delivers ETL/ELT pipelines, data lake architectures, streaming systems, and warehouse optimization.

Skills We Vet

  • ETL/ELT Pipeline Design: Expert
  • SQL & Data Modeling: Expert
  • Apache Spark / Airflow: Advanced
  • Cloud Data Services (BigQuery, Redshift): Advanced

Typical Projects

  • Data Pipeline Build: End-to-end data pipeline with extraction, transformation, quality checks, and warehouse loading. (80-180 hrs)
  • Data Warehouse Design: Dimensional model data warehouse with star schemas, slowly changing dimensions, and BI integration. (100-200 hrs)
  • Real-Time Streaming: Event streaming pipeline with Kafka, schema registry, and real-time aggregations. (90-180 hrs)

Hourly Rates

  • AI PM: $2/hr — AI agent manages the project end-to-end with automated code reviews, testing, and deployment.
  • Live PM: $3/hr — A human project manager coordinates your project with AI-augmented development workflows.
  • Live PM + Dev: $5/hr — Dedicated human PM plus senior developer oversight for mission-critical projects.

Hiring Process

  1. Submit Your Requirements: Describe your project scope, technical needs, and timeline. Our AI analyzes your requirements and identifies the ideal skill profile.
  2. AI-Matched Talent Selection: Our platform matches you with pre-vetted developers whose expertise aligns with your tech stack, industry, and project complexity.
  3. Technical Vetting & Trial: Review candidate profiles, past work, and skill assessments. Start with a small paid trial task to validate the fit before committing.
  4. Kick-off & Ongoing Delivery: Once confirmed, your developer is onboarded immediately. Track progress via real-time dashboards, milestone reviews, and daily stand-ups.

Frequently Asked Questions

What tools do your data engineers use?
Our data engineers work with Airflow, dbt, Spark, Kafka, and cloud-native services like BigQuery, Redshift, and Snowflake.
Can they handle real-time data processing?
Yes. Our engineers build streaming pipelines using Kafka, Flink, and cloud-native streaming services for sub-second latency.
Do they design data models?
Absolutely. Our data engineers design dimensional models, data vault architectures, and normalized schemas tailored to your analytics needs.