Data Engineer

21 hours ago

India Steps AI Full time

Location: India (Hyderabad - Preferred/Remote Flexibility)

Type: Full time, Paid

The Role

We're looking for an AWS focused Data Engineer with hands-on experience building production-grade pipelines at scale (terabytes of data). The ideal candidate has 1–2 years of experience in data engineering and is excited to solve tough data problems in a fast-paced startup environment.

What You Will Do

  • Design, build, and maintain production-level data pipelines that handle terabytes of structured and unstructured data.
  • Own end-to-end ETL/ELT processes, ensuring reliability, scalability, and high availability.
  • Work with AWS services (S3, EC2, RDS, DynamoDB, Athena, Redshift, etc.) to power large-scale data workflows.
  • Collaborate closely with AI/ML teams to support model training, retrieval-augmented generation (RAG), and analytics pipelines.
  • Continuously monitor, optimize, and improve data workflows for performance and cost efficiency.
  • (Nice to have) Use Apache Airflow or similar orchestration tools to manage workflows.

What we are looking for

  • 1–2 years of professional experience as a Data Engineer (or related role).
  • Proven experience building and running production pipelines at terabyte scale
  • Proficiency with Python and SQL for data engineering.
  • Strong knowledge of AWS cloud services and big data best practices.
  • Bonus: Airflow, Spark, or other orchestration/processing frameworks.
  • A self-starter who thrives in a fast-moving startup environment.

About Us:

Steps AI is building AIDE, the world's smartest AI web widget and Chat Platform that powers multi-agent copilots for businesses across industries. Our platform ingests, processes, and analyzes massive datasets across multiple sources to deliver real-time, intelligent insights.

Why Join StepsAI:

  • Work on real, production-scale data problems from day one.
  • Be part of a fast-growing AI startup with global reach.
  • Collaborate with a world-class team across AI, data, and product.

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