Senior Manager Data Engineering

Amgen Inc. (IR); Hyderabad; On-site; INR 4,000,000 - 6,600,000; Full time

Job summary

Amgen Inc. in Hyderabad seeks a Senior Manager – Data Engineering (EDSE) to lead strategic data initiatives, guide high-performing teams, and deliver enterprise-scale data platforms and products that enable analytics, AI, and digital transformation across Finance, Supply Chain, R&D, and Operations.

You will shape the Enterprise Data Fabric implementation, governance practices, and metadata management while mentoring engineers to foster technical excellence in a global, multi-vendor environment.

Qualifications

• 12+ years of experience in data engineering, data platforms, analytics engineering or related fields.
• 5+ years of leadership experience managing engineering teams and large-scale delivery programs.
• Strong experience with Databricks, Spark, PySpark, SQL, Python, AWS, and cloud-native data architectures.
• Proven ability to build enterprise-scale data platforms, data products, and integration solutions.
• Strong understanding of Data Fabric, Data Mesh, Lakehouse, metadata management, and governance.
• Experience working in Agile or SAFe delivery environments.

Responsibilities

• Lead and develop data engineering teams responsible for enterprise data products, platforms, and data solutions.
• Oversee design, development, deployment, and support of scalable data products and pipelines.
• Lead implementation of the Enterprise Data Fabric (EDF) and governance initiatives.
• Champion AI and automation to improve engineering efficiency and business value.
• Oversee performance management, career development, and talent acquisition across global teams.

Skills

Leadership

Stakeholder management

Agile / SAFe

Data engineering strategy

Tools

Databricks

Spark

PySpark

SQL

Python

AWS

Job description

Senior Manager – Data Engineering (EDSE)

About the Role

Let's do this. Let's change the world. We are looking for an experienced Senior Manager, Data Engineering to lead strategic data engineering initiatives within Enterprise Data Strategy & Engineering (EDSE). This role will guide high-performing engineering teams, deliver enterprise-scale data platforms and data products, modernize the Enterprise Data Fabric (EDF), and enable advanced analytics, AI, and digital transformation across Finance, Supply Chain, Research & Development, Operations, and other business domains.

Key Responsibilities

• Strategic Leadership Lead and develop data engineering teams responsible for enterprise data products, platforms, and mission-critical data solutions. Define and execute the domain data engineering roadmap in alignment with EDSE and enterprise priorities. Advance modern data engineering, cloud, AI, automation, and observability capabilities. Collaborate with business stakeholders, product teams, architecture, and platform engineering groups to deliver measurable business outcomes.
• Delivery & Execution Oversee the design, development, deployment, and support of scalable data products and pipelines. Ensure strong delivery across build, enhancement, RunOps, and KTLO activities. Manage commitments, capacity, priorities, risks, and vendor execution. Set engineering standards, quality practices, and performance measures across the team.
• Enterprise Data Platform & Architecture Lead implementation of the Enterprise Data Fabric (EDF), semantic layer, data products, and governance initiatives. Work with Enterprise Data Architecture and Platform Engineering teams to deliver scalable, secure, and reusable solutions. Promote metadata-driven engineering, automation, observability, data quality, and governance practices.
• AI & Innovation Champion AI, traditional ML, Generative AI, Agentic AI, and automation to improve engineering efficiency and business value. Assess and adopt emerging technologies that accelerate delivery, improve data accessibility, and strengthen platform reliability. Drive innovation through reusable accelerators, engineering frameworks, and platform modernization.
• People Leadership Build, mentor, and develop high-performing data engineering teams. Create a culture of technical excellence, collaboration, innovation, and continuous learning. Oversee performance management, career development, succession planning, and talent acquisition. Lead global, multi-vendor delivery teams aligned to organizational goals.

Required Qualifications

• 12+ years of experience in data engineering, data platforms, analytics engineering, or related fields.
• 5+ years of leadership experience managing engineering teams and large-scale delivery programs.
• Strong experience with Databricks, Spark, PySpark, SQL, Python, AWS, and cloud-native data architectures.
• Proven ability to build enterprise-scale data platforms, data products, and integration solutions.
• Strong understanding of Data Fabric, Data Mesh, Lakehouse, metadata management, and governance.
• Experience working in Agile or SAFe delivery environments.
• Excellent communication, stakeholder management, and leadership capabilities.

About Amgen

Amgen is committed to unlocking the potential of biology for patients suffering from serious illnesses by discovering, developing, manufacturing and delivering innovative human therapeutics. This approach begins by using tools like advanced human genetics to unravel the complexities of disease and understand the fundamentals of human biology.

Amgen focuses on areas of high unmet medical need and leverages its biologics manufacturing expertise to strive for solutions that improve health outcomes and dramatically improve people's lives.

A biotechnology pioneer since 1980, Amgen has grown to be one of the world's leading independent biotechnology companies, has reached millions of patients around the world and is developing a pipeline of medicines with breakaway potential.

For more information, visit www.amgen.com and follow us on www.twitter.com/amgen