Job Description

About the Organization-

Impetus Technologies is a digital engineering company focused on delivering expert services and products to help enterprises achieve their transformation goals. We solve the analytics, AI, and cloud puzzle, enabling businesses to drive unmatched innovation and growth.

Founded in 1991, we are cloud and data engineering leaders providing solutions to fortune 100 enterprises, headquartered in Los Gatos, California, with development centers in NOIDA, Indore, Gurugram, Bengaluru, Pune, and Hyderabad with over 3000 global team members. We also have offices in Canada and Australia and collaborate with a number of established companies, including American Express, Bank of America, Capital One, Toyota, United Airlines, and Verizon.

Job Description

We are seeking a skilled Data Engineer with 2–5 years of hands-on experience in designing, building, and maintaining scalable data solutions.

Key Requirements

  • 2–5 years of professional experience as a Data Engineer
  • Strong hands-on expertise with Databricks and Apache Spark (PySpark)
  • Proficient in Python for data engineering and ETL development
  • Proven experience in building, optimizing, and managing ETL pipelines
  • Experience working with at least one major cloud platform (AWS, Azure, or GCP)
  • Familiarity with Delta Lake and optimized data storage formats
  • Solid understanding of Generative AI fundamentals, including LLMs, embeddings, and RAG concepts

Good to Have

  • Hands-on experience with Generative AI frameworks such as LangChain, LangGraph, or similar
  • Experience working with vector databases like PGVector, Pinecone, or Chroma
  • Knowledge of data orchestration and workflow tools such as Airflow or Databricks Workflows

Roles & Responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL workflows
  • Work extensively with Databricks and Apache Spark to process large-scale datasets
  • Implement and optimize data storage using Delta Lake and cloud-based solutions
  • Collaborate with cross-functional teams to support analytics and AI-driven use cases
  • Contribute to GenAI-enabled data solutions by applying concepts such as embeddings and RAG

Interested candidates can directly share their resume at for quick response.

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