Analyst - Data Quality

Posted 6 Hours Ago
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Chennai, Tamil Nadu, IND
In-Office
Entry level
Biotech • Pharmaceutical
The Role
Implements data validation and quality controls across enterprise data platforms using SQL and Python. Builds Power BI monitoring dashboards, investigates root causes across pipelines and source systems, documents validation logic, supports metadata and governance initiatives, and collaborates with engineers, product managers, and business teams to improve data reliability and AI readiness.
Summary Generated by Built In
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.


Call to Action:

Step into a role where your craft turns data into decisive action—join us to build the trusted data foundation that advances science, accelerates decisions, and elevates your career!

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.

Skills Required

  • Quantitative bachelor's degree or equivalent experience in Engineering, Statistics, Applied Math, Computer Science, Data Science, Economics, or a related field
  • 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
  • Hands-on experience with a data warehouse, data lake, and Databricks
  • Strong SQL skills, including joins, aggregations, and query optimization
  • Basic to intermediate Python experience for scripting, automation, or data processing
  • Strong documentation, communication, and customer collaboration skills
  • Experience with data observability tools or monitoring frameworks
  • Exposure to AWS, Microsoft Azure, Snowflake, or Amazon Redshift
  • Experience with data pipelines, ETL/ELT processes, or data transformation workflows
  • Experience with metadata-driven validation or data contracts
  • Familiarity with Collibra or similar enterprise data governance platforms
  • Experience in large global organizations or regulated industries
  • Exposure to pharmaceutical, healthcare, or commercial analytics datasets
  • Experience with Power BI, Excel, or other BI tools for data quality monitoring and reporting

AstraZeneca Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AstraZeneca and has not been reviewed or approved by AstraZeneca.

  • Fair & Transparent Compensation — Pay is considered competitive across many roles when total rewards are factored in. Senior scientific and leadership bands are described with high ranges that reinforce competitiveness at upper levels.
  • Strong & Reliable Incentives — Bonuses, equity eligibility in many salaried roles, and solid sales on‑target earnings with upside are emphasized as meaningful parts of compensation. These elements boost overall value even where base pay is not the very highest.
  • Retirement Support — A 401(k) program with a strong company match and immediate vesting is repeatedly cited as a standout. Generous retirement support is viewed as enhancing the total package relative to peers.

AstraZeneca Insights

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The Company
HQ: Gaithersburg, MD
70,000 Employees
Year Founded: 1999

What We Do

We're transforming the future of healthcare by unlocking the power of what science can do for people, society and the planet.

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