Hybrid Senior Data Engineer

Posted last week

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About the role

  • Dedicate your time to developing, testing, and maintaining high-quality, scalable ETL/ELT data pipelines using Python, PySpark, and Databricks on AWS
  • You will lead the development of new data features and services across the full product lifecycle, from architectural design to deployment including technologies like Terraform, spark structured streaming, dlt, etc.
  • Create CI/CD controlled data engineering deployments using Databricks Asset Bundles and leverage Databricks serverless compute with cost optimization techniques to deliver performant data products
  • Work within a fast-paced agile team, collaborating closely with Product Managers, Data Scientists, and fellow engineers to solve complex data challenges. You will help ensure the quality, integrity, and security of data throughout the data lifecycle, implementing best practices in data governance
  • Take technical ownership of major components of our data platform architecture. You will lead design discussions, ensuring our data systems are secure, scalable, and maintainable
  • Analyse workloads, queries, clusters/warehouses, jobs, and services to identify inefficiencies and savings opportunities
  • Implement continuous monitoring and intelligence dashboards for cost and performance optimization
  • Stay ahead of new Snowflake/Databricks features and translate them into marketable product differentiators

Requirements

  • Extensive experience with data engineering; **DataBricks & DBT** (Mandatory)
  • Proven expertise in platform internals:
  • **Databricks**: clusters, jobs, Delta Lake, Spark optimization, autoscaling, Unity Catalog
  • Strong **SQL + Python skills** for automation, monitoring, and recommendation logic
  • Experience with frameworks like **Terraform & Airflow**
  • Track record of delivering performance gains and cost savings through platform-level optimizations
  • Startup mindset: hands-on, automation-driven, customer-value obsessed
  • **Preferred but not mandatory**
  • Databricks Certification
  • Familiarity with compliance frameworks like SOC2, GDPR
  • Knowledge of LLMs and AI frameworks

Benefits

  • Mental health and well-being initiatives
  • Generous parental (including secondary) leave policy
  • Flexibility to work in a Hybrid model (2 days in-office)
  • Paid birthday, study and volunteering leave every year
  • Sponsored social clubs, team events, and celebrations
  • Employee Resource Groups (ERG) to help you connect and get involved
  • Investment in your personal growth offering training for your advancement

Job title

Senior Data Engineer

Job type

Experience level

Senior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

HybridPuneIndia

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