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Amgen · Global, India officeAll 40 open roles ›

Sr. Associate Software Engineer

Hyderabad · On-site · Posted
Location
Hyderabad
Level
Senior
Experience
4–7 years
Pay
Not listed
Workplace
On-site
Posted
4 months ago
Status
Open · checked 11h ago

On a laptop, OpenRoles fills Amgen's form from your resume — you check it and press Submit. Sign up free now and it's ready when you get there.

Skills mentioned in the posting

  • ETL
  • Databricks
  • Spark
  • CI/CD
  • PySpark
  • SQL
  • Python

Career Category

Engineering

What you will do

Let’s do this. Let’s change the world.

In this vital role as Data Engineer at Amgen, you will play a key role in designing, building, and maintaining scalable data solutions that enable trusted insights and support critical business decisions.

This position is focused on supporting the OUS Field Engagement Team, working closely with stakeholders across the JAPAC and ELMAC regions. You will collaborate with global and regional teams to deliver data solutions that support field operations, customer engagement, and analytics use cases in a complex, multi-region environment.

You will work in an Agile (SAFe) environment, contribute to supporting enterprise data initiatives primarily built on Informatica ETL, including the future migration from Informatica to Databricks.

Key Responsibilities

  • Design, develop, maintain, and optimize ETL pipelines using Informatica, ensuring high data quality, performance, and reliability
  • Support and contribute to the future transition of Informatica workloads to Databricks (Spark, Delta Lake)
  • Build and enhance data pipelines for ingestion, transformation, and processing of large-scale datasets supporting OUS Field Engagement use cases
  • Collaborate with Data Architects, Business SMEs, Product Owners, and Senior Data Engineers across JAPAC and ELMAC regions to deliver end-to-end data solutions
  • Participate actively in a SAFe/Agile team, contributing to PI planning, sprint execution, and continuous improvement
  • Support data governance, metadata management, and data quality initiatives
  • Identify, troubleshoot, and resolve complex data issues across systems
  • Apply best practices for coding, testing, documentation, and reusable component design
  • Translate business and technical requirements into well-structured development tasks
  • Execute unit and integration testing to ensure solution robustness and compliance with quality standards
  • Monitor data pipelines and applications, supporting ongoing maintenance and performance optimization
  • Contribute to CI/CD and DevOps practices for data engineering solutions
  • Mentor junior team members and promote data engineering best practices

What we expect of you

We are all different, yet we all use our unique contributions to serve patients.

Basic Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, IT, or a related field
  • 4–7 years of relevant data engineering experience, with strong hands-on ETL background

Preferred Qualifications

  • Strong experience with Informatica (PowerCenter, IICS)
  • Exposure to Databricks, Apache Spark, PySpark, or Spark SQL
  • Familiarity with SAFe or Agile delivery models
  • Experience or exposure to Master Data Management (MDM)
  • Experience with Veeva systems (nice to have)
  • Experience supporting Field Engagement or Commercial data domains (preferred)

Must-Have Skills

  • Advanced ETL development experience, particularly with Informatica
  • Strong SQL skills for data extraction, transformation, and analysis
  • Solid understanding of data modeling and entity relationships
  • Working knowledge of Python and/or PySpark
  • Experience supporting production data pipelines and resolving data issues
  • Ability to work effectively in global, cross-regional teams

Soft Skills

  • Strong problem-solving and analytical mindset
  • Excellent communication and collaboration skills, including with global stakeholders across regions
  • Proven team player with experience in Agile/SAFe environments
  • High attention to detail and commitment to data quality
  • Ability to manage priorities and work in a fast-paced environment
  • Willingness to mentor junior engineers and share knowledge
  • Adaptable to evolving technologies and business needs

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