Analyst - Data Quality

AstraZeneca; Chennai District; Hybrid; INR 700,000 - 1,200,000; Full time

Job summary

AstraZeneca in Chennai is seeking an Analyst - Data Quality to transform raw enterprise data into trusted insights that accelerate decisions impacting patients worldwide. Based in Chennai, you will strengthen data platforms, implementing validation, tracking data health, and delivering AI-ready data products.

You will sharpen SQL, Python, and cloud skills while collaborating with data engineers, product managers, and governance teams.

Qualifications

• Bachelor's degree in Engineering, Statistics, Applied Math, CS, DS, Economics or related.
• 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/ELT operations, data warehouse, data lake, and Databricks.
• Strong SQL skills including joins, aggregations, and optimization.
• Basic to intermediate Python for scripting, automation, or data processing.
• Strong documentation and collaboration skills.

Responsibilities

• Implement data validation and quality rules using SQL to ensure completeness, accuracy, and consistency; 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 and SLA adherence.
• Investigate issues across source systems, ingestion pipelines, and transformation layers; 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; support metadata tagging and alignment for AI-ready data products.
• Partner with senior team members, Data Product Managers, Market squads, and governance teams to align on quality standards and remediation priorities.
• Find opportunities to optimize queries, streamline quality controls, and automate routine checks to improve efficiency and reduce defects.
• Translate technical findings into business-relevant recommendations that enhance downstream analytics and decision-making.

Skills

SQL proficiency

Python scripting

Data quality

Data analytics

Documentation

Power BI

ETL experience

Education

Bachelor's degree in a quantitative field

Tools

Databricks

Power BI

AWS/Azure

Snowflake

Job description

Analyst - Data Quality

Career Level: C3

Introduction to role:

Are you ready to turn raw enterprise data into trusted insights that accelerate decisions impacting patients worldwide? As an Analyst - Data Quality based in Chennai, you will strengthen the backbone of our global data platforms, ensuring our data products are accurate, complete, and reliable for analytics and reporting that matter.

You will implement and monitor data quality controls across shared data platforms, working closely with data engineers and business partners. Can you see yourself diagnosing issues at their source and partnering with teams to deliver fixes that stick? Your work will directly improve the performance of dashboards and critical metrics used across the enterprise, enabling faster, better decisions.

In this role, you will sharpen your SQL, Python, and cloud data skills while contributing to AI-ready data products. You will join a collaborative, fast paced environment where diverse perspectives and digital innovation drive meaningful outcomes.

Accountabilities:

• Data Quality Management: Implement data validation and quality rules using SQL to ensure completeness, accuracy, and consistency; develop reusable scripts and queries to automate checks and improve coverage.
• Monitoring and Reporting: 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.
• Issue Triage and Root Cause Analysis: Investigate issues across source systems, ingestion pipelines, and transformation layers; collaborate with data engineering and upstream teams to validate fixes and prevent recurrence.
• Documentation and Governance: Maintain clear documentation for rules, validation logic, benchmark definitions, and monitoring processes; support metadata tagging, taxonomy and ontology alignment to enable AI-ready data products in partnership with product managers and governance teams.
• Customer Collaboration: 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.
• Continuous Improvement: Find opportunities to optimize queries, streamline ETL/ELT quality controls, and automate routine checks to improve efficiency and reduce defects over time.
• Business Impact: Translate technical findings into business-relevant recommendations that enhance downstream analytics, reporting reliability, and decision-making speed.

Essential Skills/Experience:

• Education: Quantitative bachelor’s degree or equivalent experience (Engineering, Statistics, Applied Math, Computer Science, Data Science, Economics, or related).
• 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, as well as 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.

Desirable Skills/Experience:

• 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.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Join a high-performing, digitally savvy team where data precision fuels real-world impact. We bring diverse specialists together to solve complex problems, using modern platforms and innovations to streamline how the enterprise operates and to prepare for what’s next. Here, you will sit shoulder-to-shoulder with engineers, product managers, and analysts, using design thinking and data-driven decision-making to build trusted, AI-ready data products that speed better outcomes for patients. We value curiosity and ambition as much as kindness and collaboration, offering the freedom to own your ideas and the support to grow in new directions.

Date Posted 08-Oct-2026

Closing Date 13-Oct-2026

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.