Senior Analyst - Data Quality

AstraZeneca; Chennai District; Hybrid; INR 1,600,000 - 2,100,000; Full time

Job summary

AstraZeneca is seeking a Senior Analyst - Data Quality in Chennai to turn raw data into trusted intelligence for decisions across science, operations and markets.

You will design reusable validation frameworks, automation utilities and scalable monitoring to reduce data risk and increase transparency for customers, enabling AI-ready data products and informed decision-making.

Qualifications

• Bachelor’s degree in a quantitative field.
• 5+ years in data quality or ETL/data analytics roles.
• Experience building data quality controls and validation rules.
• Experience with modern data warehouses and data lake architectures.
• Hands-on SQL development and performance optimization.

Responsibilities

• Design and implement SQL and Databricks validations per business rules.
• Build reusable Python utilities for data validation and monitoring.
• Create Power BI dashboards and reports for data quality metrics.
• Lead root cause analysis across data pipelines and source systems.
• Document data quality rules, contracts and metric definitions.

Skills

SQL

Python

ETL

Data quality

Databricks

Spark

Cloud platforms

Education

Bachelor's degree

Tools

Power BI

Azure

Snowflake

SQL Databases

Job description

Job Title: Senior Analyst - Data Quality

Career Level: D1

Introduction to role:

Are you ready to turn raw data into trusted intelligence that accelerates decisions and improves patient outcomes? As a Senior Analyst - Data Quality based in Chennai, you will build the enterprise-grade controls that make our global data products accurate, reliable and ready for advanced analytics and AI. Your work will unlock confident decisions at scale across science, operations and markets.

You will join a high-performing, digitally savvy team that thrives on inclusive collaboration and fast learning. By designing reusable validation frameworks, automation utilities and scalable monitoring, you will reduce data risk, speed up delivery and create transparency for customers. How will you translate complex pipelines into simple, measurable quality signals that teammates and leaders can act on fast?

Accountabilities:

• Data Quality Engineering: Design, develop and implement SQL and Databricks validations aligned to business rules and quality standards, ensuring completeness, consistency and reliability across shared data platforms.
• Reusable Frameworks and Automation: Build modular scripts, utilities and reusable components in Python to scale data validation and monitoring across multiple pipelines and products.
• Monitoring and Reporting: Create and maintain Power BI dashboards, critical metric scorecards and reports that give customers self-service insight into data quality performance, SLA alignment and data health trends; provide clear narratives and alerts that drive action.
• Issue Triage and Root Cause Analysis: Lead investigations across source systems, ingestion pipelines and transformation layers to identify anomalies and systemic issues; partner with engineering and upstream teams to implement remediation and preventative controls.
• Data Governance and Documentation: Maintain robust documentation for data quality rules, validation logic, data contracts and critical metric definitions; support metadata tagging, taxonomy and ontology alignment to enable AI‑ready data products.
• Customer Partnership and Enablement: Work closely with data product managers and multi‑functional teams to embed quality by design, prioritize backlogs and communicate outcomes that influence decision‑making.
• Continuous Improvement and Standards: Standardize guidelines for data quality across cloud platforms, continuously improve performance and cost efficiency, and help set enterprise‑wide quality benchmarks that scale with growth.

Essential Skills/Experience:

• Education: Quantitative bachelor’s degree (Engineering, Statistics, Applied Math, Computer Science, Data Science, Economics, or related).
• 5+ years of experience in data quality management, ETL data management systems, or data analytics roles.
• Solid experience implementing data quality controls, data validation rules, or data integrity monitoring frameworks.
• Demonstrated experience in ETL pipeline operations and management, with handson knowledge of modern data warehouse and data lake architectures.
• Advanced SQL development skills including CTEs, window functions, complex joins, and performance optimization.
• Experience working with distributed data processing platforms such as Databricks, Apache Spark, or PySpark.
• Strong Python programming skills for automation, scripting, data processing.
• Experience working with cloud data platforms such as AWS, MS-Azure, Snowflake, or Amazon Redshift.
• Strong documentation, communication, and customer collaboration skills.

Desirable Skills/Experience:

• Experience with data observability tools or monitoring frameworks.
• 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:

Here, your expertise in data quality fuels decisions that matter—pairing cutting‑edge cloud technologies with a culture that values curiosity, collaboration and momentum. You will work where diverse perspectives meet to solve complex problems, building AI‑ready data products that strengthen how we operate and ultimately serve patients. We combine ambition with support, valuing kindness alongside high standards, so you can take smart risks, learn quickly and see your impact ripple across a global enterprise.

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.