Associate Data Engineer

Posted 7 Days Ago
Be an Early Applicant
Chennai, Tamil Nadu, IND
In-Office
Senior level
Biotech • Pharmaceutical
The Role
Operate, monitor, and improve cloud ETL pipelines to ensure timely, high-quality data across global markets. Maintain Python/PySpark transformations, manage AWS S3/Redshift/EMR storage and processing, trigger and validate API jobs, troubleshoot incidents, perform root-cause analysis, collaborate with data providers/DevOps, keep documentation and schedules current, and drive automation and quality controls to increase reliability and throughput.
Summary Generated by Built In
Job Title: Associate Data Engineer
 
GCL : C3
 

Introduction to role:
 

Are you ready to keep mission-critical data flowing at global scale and turn incidents into improvements that boost reliability? As an Associate Data Engineer, you will run and enhance the cloud pipelines that power decisions across 85+ markets, ensuring timely, high-quality data reaches the people who need it most.

You will join a high-performing, digitally savvy team that partners across the enterprise to drive speed and precision. Your focus on automation, monitoring, and rapid incident response will translate into trusted data and smoother releases—accelerating how we deliver life-changing medicines. Can you picture yourself orchestrating robust pipelines that help colleagues move faster with confidence?
 

Accountabilities:
 

Pipeline Operations: Implement and monitor end-to-end data pipelines and ETL jobs across multiple stages to ensure on-time, high-quality delivery at scale.

Data Transformation: Maintain and modify Python (Pandas, PySpark) scripts in line with evolving business needs to improve data quality and performance.

Cloud Data Management: Manage data storage and protected data exchanges across AWS S3, Redshift, and EMR, keeping data flows accurate and compliant.

API Orchestration: Trigger and validate jobs using Postman and other API interfaces to keep schedules on track and detect issues early.

Data Flow Governance: Track inbound and outbound files, log exceptions, and maintain observability to prevent and detect data breaks.

Incident Response and Root Cause Analysis: Investigate and remediate pipeline failures or delays, implement durable fixes, and drive automation that reduces repeat incidents.

Teamwork and Collaborator Management: Work closely with data providers, data custodians, and DevOps teams to assure pipeline health and data accuracy across global collaborators.

Documentation and Versioning: Keep pipeline documentation, job schedules, and technical configurations up to date; support code enhancements and environment updates.

Quality Control: Participate in data quality procedures with Data Stewards to validate releases and safeguard trust in data products.

Continuous Improvement: Identify and implement opportunities to standardize, simplify, and automate operations, increasing reliability and throughput over time.
 

Essential Skills/Experience:
 

Python (PyCharm, Pandas, PySpark) for maintaining ETL scripts and automation routines
 

Postman for testing and triggering API-based job executions
 

SQL proficiency using tools such as DBeaver to query and validate relational data

AWS services proficiency across Redshift, S3, and EMR for processing and storage
 

WinSCP or equivalent tools for secure file transfers
 

Proactive, structured approach to monitoring and troubleshooting

Strong programming and analytical problem-solving abilities

Excellent documentation and organizational skills

Ability to work independently and coordinate across functional teams

Desirable Skills/Experience:
 

Familiarity with Git and version control systems
 

5–8 years of experience in data engineering, production support, or data operations
 

Background handling large-scale data workflows in cloud environments
 

Experience working in pharmaceutical or healthcare data ecosystems

Consistent track record resolving performance bottlenecks and job failures

Familiarity with DevOps principles and agile ways of working
 

Why AstraZeneca:
 

Here, data engineering fuels real-world impact. You’ll work with modern cloud platforms and digital tools, side by side with unexpected combinations of experts—engineers, data stewards, and market teams in the same room—turning bold ideas into operational reality. We move with urgency and clarity, blending imagination with rigor to strengthen how the business runs today while preparing for tomorrow. Your contribution will help colleagues across the globe focus on what matters most, translating into faster, smarter decisions that ultimately benefit patients. We value patience alongside ambition, and we back curiosity with the support and autonomy needed to deliver significant results.

Call to Action:

If you’re ready to build resilient workflows that drive faster decisions and tangible patient impact, step forward and build what reliable data can make possible!

Date Posted

12-Aug-2026

Closing Date

27-Aug-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

  • Proficiency in Python (PyCharm, Pandas, PySpark) for ETL and automation
  • Experience using Postman for testing and triggering API-based job executions
  • SQL proficiency (using tools such as DBeaver) to query and validate relational data
  • AWS experience across S3, Redshift, and EMR for storage and processing
  • Experience with secure file transfer tools (WinSCP or equivalent)
  • Proactive, structured approach to monitoring and troubleshooting data pipelines
  • Strong programming and analytical problem-solving abilities
  • Excellent documentation and organizational skills
  • Ability to work independently and coordinate across functional teams
  • Familiarity with Git and version control systems
  • 5-8 years of experience in data engineering, production support, or data operations
  • Background handling large-scale data workflows in cloud environments
  • Experience working in pharmaceutical or healthcare data ecosystems
  • Track record resolving performance bottlenecks and job failures
  • Familiarity with DevOps principles and agile ways of working

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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