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Immediate -SSE (Python +Databricks+Pyspark+ MLOps+SQL)-US Product Comp

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Immediate -SSE (Python +Databricks+Pyspark+ MLOps+SQL)-US Product Comp

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Immediate -SSE (Python +Databricks+Pyspark+ MLOps+SQL)-US Product Comp

Skills

Google Cloud PlatformSQL QueriesData EngineeringFlaskPythonDatabricksAIAWSGitHubFastAPIPySparkTerraform

2 months ago

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Important information


Contract type:

Permanent

Location:

Pune, Maharashtra, India

Work mode:

Remote

Published on:

18 August 2026

What they need


Role & responsibilities

  • Build and maintain multi-cloud Databricks infrastructure using Terraform and Databricks functionality across mostly AWS, and GCP.

  • Contribute to Unity Catalog administration including general best practices, metastores, workspaces, catalog, schema infrastructure and Databricks Asset Bundles.

  • Act as a platform engineer, building self-service tools and 'golden paths' for other teams, and actively contribute to community enablement through documentation, training, and cross-team knowledge sharing.

Preferred candidate profile

Cloud & Infrastructure:

  • 5 to 8 years of software engineering experience, ideally in infrastructure or data platform roles.
  • Proficiency in Python/PySpark and strong knowledge of SQL.
  • Experience with Terraform or similar Infrastructure-as-Code (IaC) tools.
  • Strong knowledge of at least one cloud platform (GCP/AWS)
  • Solid CI/CD experience.

Data & MLOps Expertise:

  • Strong Background in Databricks, specifically Unity Catalog, medallion architecture, and Databricks Asset Bundles (DABs).
  • Proficiency in Python and API frameworks such as FastAPI or Flask.
  • Strong experience designing, developing, and maintaining RESTful APIs.
  • Good understanding of data engineering concepts such as data modeling and workflow orchestration.
  • Experience with MLOps and Data Engineering like having worked on Spark/Delta Lake/MLflow/ETL frameworks (e.g., Fivetran, Lakeflow Connect).

Operational Excellence:

  • Experience with Github workflows, including container versioning.
  • Proficiency with incident management and observability tools (e.g., PagerDuty, system monitoring).

Mindset & Collaboration:

  • An AI as a partner mindset.
  • A collaborative approach, including asking questions, navigating unclear requirements, and actively contributing to knowledge sharing/community enablement.

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