FinOps Data Analyst - Azure Databricks, Pyspark, Data Engineering -WFO

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