ETL Technical Product Owner / Manager

Role Summary:

To lead a vibrant data team that is creating & maintaining re-usable data pipelines using Databricks, PySpark & GCP. The role will involve managing the work end to end, interaction and co-ordination with multiple stakeholders including US counterparts & other vendor team members.

Essential Responsibilities

• Lead the overall data engineering lifecycle including proof of concepts, architecture, design, development, test, deployment and maintenance of data pipeline and solutions
• Establish and implement standardized guidelines for ETL and data architecture, ensuring consistency and efficiency
• Guide team to create frameworks that guarantee data quality, handle errors effectively, provide audit controls, and offer reusable transformation structures
• Lead team to apply a comprehensive, enterprise-wide approach to building data models and data management strategies, ensuring seamless integration across upstream and downstream applications
• Transform business requirements into creative and practical data solutions that address constraints and optimize processes.
• Effectively communicate with business users, US team, architects, data analysts, and other teams to ensure data solutions meet their needs and align with overall objectives.
• Lead and mentor multiple data engineering teams to achieve project objectives & deliverables
• Manage day to day operation and ensure adherence to process, scope, quality and timelines
• Participate in review of requirements, architecture & design
• Highlight risks and concerns, work with US managers to establish alignment, contingency and mitigation plans as required
• Constantly looking to identify impediments early, actively working to resolve those impediments, and escalate when needed
• Track delivery statuses, project progress and take ownership of critical incidents till completion
• Take ownership and accountability of critical projects (for work executed in India)
• Publish regular status to leadership team highlighting risks & issues among other things
• Other duties as assigned or requested - approximately 50% technical and 50% management

The experience we are looking to add to our team

Required

• 10 to 14 years of overall experience with majority of them in Data engineering
• Experience managing complex data projects and programs involving data engineering, ingestion, transformation, aggregation, modeling and storage
• Experience in managing enterprise grade ETL/ELT solutions using Pyspark / GCP DataProc / Databricks etc.
• Experience building, mentoring, and managing high performing teams spread across multiple geographical locations
• Strong customer focus, communication, collaboration and problem-solving skills
• Excellent communication, confidence & attitude
• Experience in big data technologies (HDFS, Spark, Pyspark, Databricks etc)
• Experience in leading a team and delivering complex projects involving creation and maintenance of data pipelines.

Good to have

• Google Cloud knowledge / experience
• Knowledge on tools like Iceberg, DBT, Starburst
• Agile experience
• Healthcare experience.