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FinOps Data Analyst - Azure Databricks, Pyspark, Data Engineering

Genpact

RemoteFull timeMid levelPosted today
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About the role

Inviting applications for the role of Senior Data Engineer

Responsibilities

  • Analyze large-scale structured and unstructured datasets using Databricks and PySpark.
  • Develop cost and usage reports using Databricks SQL and PySpark.
  • Develop PySpark notebooks to process large-scale cloud billing and usage data.
  • Build and maintain FinOps data models within Databricks Lakehouse.
  • Ingest cloud billing data from AWS CUR, Azure Cost Management, and vendor sources.
  • Create curated FinOps datasets for reporting and forecasting.
  • Optimize data processing jobs for performance and cost efficiency.
  • Build scalable Databricks notebooks and workflows.
  • Develop ETL/ELT processes for FinOps data integration.
  • Leverage Delta Lake for cost analytics datasets.
  • Optimize Spark jobs and SQL workloads.

Qualifications we seek in you!

Minimum Qualifications

  • Bachelors degree in computer science, Information Technology, Data Science, Statistics, Mathematics, or related field.
  • 10–15 years of experience in Data Analytics, Business Intelligence, or Data Engineering roles.
  • Experience working with enterprise-scale data platforms.
  • Experience with FinOps – Data Engineering would be preferred
  • 5+ years of experience Develop and optimize PySpark notebooks for data transformation and analysis.
  • 5+ years of experience Query and analyzing data using Databricks SQL and Spark SQL.
  • Strong business acumen and ability to connect financial data to business value
  • Excellent communication and executive presentation skills
  • Experience working with cross-functional stakeholders at senior levels

Preferred Qualifications/ Skills

  • Databricks Certified Data Analyst Associate
  • Databricks Certified Data Engineer Associate
  • Experience with FinOps and cost management tools:
  • Apptio Cloudability
  • AWS Cost Explorer
  • Azure Cost Management
  • Experience with automation tools and scripting (Python, APIs)
  • Exposure to multi-cloud enterprise environments

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