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.
Solid 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 settings

📌 Finops Data Analyst Azure Databricks, Pyspark, Data Engineering Wfo Hyderabad
🏢 Genpact
📍 Hyderabad