Data Specialist

Overview

Individual contributor data steward role in the European Gas and Power Data team, executing data stewardship, validation, lineage and governance activities so that source data is validated and quality checked before it reaches internal SMEs and external clients.

What you'll do

• Perform data validation checks, lineage tracking and metadata updates to maintain data quality, integrity and traceability.
• Execute data ingestion, validation and integration activities in alignment with governance and control standards.
• Ensure consistent adherence to enterprise data policies and governance frameworks.
• Execute defined controls and compliance requirements to safeguard data integrity and lineage.
• Support vendor data reviews and onboarding through data quality assessments, validation checks and issue resolution.
• Maintain data standardization, stewardship documentation and process artifacts to ensure accuracy and consistency.
• Execute medium-complexity stewardship and validation tasks under established guidelines, escalating exceptions when required.
• Respond to client data queries, resolving issues and coordinating issue triage with Operations and Client Services teams.
• Collaborate with Technology teams on defect resolution, enhancement requests and UAT for backend data and dataflow changes.
• Contribute to automation and AI-enabled improvements that enhance efficiency and strengthen stewardship capabilities.
• Investigate, validate, troubleshoot and support controlled updates to transformation scripts, data quality rules and pipeline logic using Python, SQL and PySpark, ensuring automated processes run to schedule and produce accurate outputs.
• Support onboarding of new datasets required by SMEs by reviewing source structures, validating expected outputs, identifying data quality risks and coordinating required pipeline or source data changes within the existing architecture.
• Support User Acceptance Testing (UAT) by validating data, coordinating test execution and assisting with defect identification and resolution.
• Ensure adherence to governance, data management standards and operating procedures by following defined controls and compliance requirements.
• Maintain high-quality documentation by updating process flows, data definitions, data dictionaries and other stewardship artifacts to ensure audit readiness and operational clarity.
• Collaborate with Data Operations and Technology teams to support governance activities, quality controls, source amendments, validation outcomes and issue remediation, serving as a liaison between governance expectations and day-to-day execution.
• Support Product and Technology teams with data requirements, validations and operational coordination throughout change cycles.
• Assist with vendor data reviews by conducting data quality checks, performing validations and coordinating onboarding processes.

What you'll need

• Intermediate Python scripting skills, including the ability to investigate, maintain, debug and support controlled updates to transformation logic, automation scripts and data quality checks.
• Intermediate SQL capability to query, reconcile, transform, validate and troubleshoot data across relational databases and pipeline outputs.
• Hands-on experience with PySpark or distributed data processing to support investigation, validation, reconciliation and quality checks across large or complex datasets.
• Understanding of cloud computing, preferably AWS.
• Working knowledge of AI/ML workflows.
• Works with metadata management and lineage tools to maintain data transparency and trace end-to-end data flows.
• Foundational familiarity with BI tools and dashboards to review outputs and identify data anomalies.
• Solid domain and process understanding.
• Understanding of data governance fundamentals, including data quality controls, stewardship roles and ownership models.
• Supports data standardization by applying consistent data definitions, formats and controlled processes.
• Working knowledge of data ingestion, transformation, validation, reconciliation and integration workflows, with the ability to investigate pipeline failures, check source-to-target accuracy, support root cause resolution and coordinate remediation actions.
• Collaborate with cross-functional teams to understand their data requirements and issues and generate innovative ideas and solutions.
• Strong attention to detail, ensuring accuracy in data, documentation and validation activities.
• Communicates clearly and collaborates effectively with cross-functional teams including Technology, Operations, Product and Vendor partners.
• Analytical mindset, critical thinking and creative problem solving, including root cause analysis of data issues.
• Learning agility, digital acumen, initiative and ownership in data stewardship activities, adapting to evolving tools and technologies while working effectively through ambiguity.
• 4+ years of relevant experience in data, analytics, operations or related functions.

Nice to have

• Working knowledge of Databricks, including notebooks, jobs, clusters and pipeline monitoring.

Details

• Location: Gurugram, Haryana, India.
• Grade level 09.