Tech Lead – Data Engineering/Data Science

5 days ago

Hyderabad, Telangana, India Simax Systems Full time ₹ 12,00,000 - ₹ 36,00,000 per year

What You'll Do

  • Lead architecture and development of
    data pipelines, warehouses, and AI-ready infrastructures
    for both internal products and client projects.
  • Design and oversee
    machine learning workflows
    supporting OCR, NLP, and predictive analytics in Simax products like
    Scribe
    ,
    Quanta
    , and
    Compass
    .
  • Guide the implementation of
    Enterprise Data Warehouse (EDW)
    solutions for global clients using AWS, GCP, or Azure.
  • Collaborate with client stakeholders to translate business challenges into
    robust data strategies and architectures
    .
  • Mentor and manage a cross-functional team of
    data engineers, analysts, and ML developers

What We're Looking For

  • 5–8 years of experience in
    data engineering & data science
    , with at least 2 years in a
    technical or team leadership role
    .
  • Strong command of
    Python, SQL, ETL frameworks (Airflow/dbt/Glue)
    , and
    cloud platforms (AWS/GCP/Azure)
    .
  • Experience with
    data warehouses
    (Snowflake, Redshift, BigQuery, Databricks) and
    machine learning frameworks
    (scikit-learn, TensorFlow, PyTorch).
  • Proven ability to manage
    end-to-end data projects
    — from design to deployment — in a client or consulting setup.
  • Excellent communication, problem-solving, and stakeholder engagement skills.

Bonus Skills:

  • Exposure to
    OCR/NLP systems
    ,
    data governance
    ,
    MLOps
    , or
    LLM-based AI solutions
    .
  • Hands-on experience with
    containerization (Docker/Kubernetes)
    and
    CI/CD for data pipelines
    .

Why Join Us

  • Lead
    data-driven innovation
    across AI products and enterprise solutions.
  • Work on cutting-edge
    AI + Data Engineering
    challenges that impact real-world systems.
  • Be part of a growing
    Data & AI team
    shaping the future of intelligent platforms.
  • Competitive compensation, performance incentives, and opportunities for growth.

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