Analyst - Data Quality

Overview

Implement and monitor data quality controls across shared enterprise data platforms, working with data engineers and business partners to keep data products accurate, complete and reliable for analytics and reporting.

What you'll do

• Implement data validation and quality rules using SQL to ensure completeness, accuracy and consistency, and develop reusable scripts and queries to automate checks and improve coverage.
• Build and maintain Power BI dashboards, critical metric scorecards and monitoring reports that track data health trends, SLA adherence and issue backlogs.
• Help customers access and interpret quality metrics to drive action.
• Investigate issues across source systems, ingestion pipelines and transformation layers, and collaborate with data engineering and upstream teams to validate fixes and prevent recurrence.
• Maintain clear documentation for rules, validation logic, benchmark definitions and monitoring processes, and support metadata tagging, taxonomy and ontology alignment in partnership with product managers and governance teams.
• Partner with senior team members, Data Product Managers, Market squads and central governance teams to align on quality standards, prioritize remediation and improve data trust at scale.
• Optimize queries, streamline ETL/ELT quality controls and automate routine checks to improve efficiency and reduce defects over time.
• Translate technical findings into business-relevant recommendations that enhance downstream analytics, reporting reliability and decision-making speed.

What you'll need

• Quantitative bachelor's degree (Engineering, Statistics, Applied Math, Computer Science, Data Science, Economics or related) or equivalent experience.
• Experience in data quality, data analytics, data management or related data roles.
• Experience implementing data validation checks, data profiling or data quality monitoring.
• Experience with ETL pipeline operations and management, and hands-on experience working on a data warehouse, data lake and Databricks.
• Strong SQL skills including joins, aggregations and query optimization.
• Basic to intermediate experience with Python for scripting, automation or data processing.
• Strong documentation, communication and customer collaboration skills.

Nice to have

• Experience with data observability tools or monitoring frameworks.
• Exposure to cloud data platforms such as AWS, Microsoft Azure, Snowflake or Amazon Redshift.
• Experience working with data pipelines, ETL/ELT processes or data transformation workflows.
• Experience with metadata driven validation or data contracts.
• Familiarity with enterprise data governance platforms such as Collibra.
• Experience working in large global organizations or regulated industries.
• Exposure to pharmaceutical, healthcare or commercial analytics datasets.
• Experience with Power BI, Excel or BI tools for data quality monitoring and reporting.

Details

• Location: Chennai, Tamil Nādu, India.
• Work mode: in-person, on average a minimum of three days per week from the office.