Senior Manager Data Engineering

Amgen · Hyderabad

  • Experience12–13 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted23 Sept 2026
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About Amgen

Amgen is hiring in Hyderabad in pharma biotech. This role looks for around 12+ years of experience.

Skills

  • Databricks
  • Apache Spark
  • PySpark
  • SQL
  • Python
  • Amazon Web Services (AWS)
  • cloud-native data architectures
  • enterprise-scale data platforms
  • data products
  • Data Fabric
  • Data Mesh
  • Lakehouse
  • metadata management
  • data governance
  • Agile
  • SAFe

The role

A data engineering manager at a biotechnology company leads enterprise data platforms and products for analytics and AI, applying Data Fabric, Databricks, and AWS. The role guides engineering teams, modernizes cloud-native data architecture, and advances governance and automation.

Full 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.