Resume and JobRESUME AND JOB
Amgen logo

Data Engineering Manager

Amgen

Data Engineering Manager

Amgen logo

Amgen

full-time

Posted: November 12, 2025

Number of Vacancies: 1

Job Description

ABOUT AMGENAmgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.ABOUT THE ROLERole Description:We are seeking a seasoned Engineering Manager (Data Engineering) to lead the end-to-end management of enterprise data assets

What you will do

  • Lead and manage the enterprise data operations team, responsible for data ingestion, processing, validation, quality control, and publishing to various downstream systems.
  • Define and implement standard operating procedures for data lifecycle management, ensuring accuracy, completeness, and integrity of critical data assets.
  • Oversee and continuously improve daily operational workflows, including scheduling, monitoring, and troubleshooting data jobs across cloud and on-premise environments.
  • Establish and track key data operations metrics (SLAs, throughput, latency, data quality, incident resolution) and drive continuous improvements.
  • Partner with data engineering and platform teams to optimize pipelines, support new data integrations, and ensure scalability and resilience of operational data flows.
  • Collaborate with data governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls.
  • Serve as the primary escalation point for data incidents and outages, ensuring rapid response and root cause analysis.
  • Build strong relationships with business and analytics teams to understand data consumption patterns, prioritize operational needs, and align with business objectives.
  • Drive adoption of best practices for documentation, metadata, lineage, and change management across data operations processes.
  • Mentor and develop a high-performing team of data operations analysts and leads.

What we expect of you

  • 9 to 12 years of experience in Computer Science, IT or related field
  • AWS Certified Data Engineer preferred
  • Databricks Certificate preferred
  • Scaled Agile SAFe certification preferred

Must-Have Skills

  • Experience managing a team of data engineers in biotech/pharma domain companies.
  • Experience in designing and maintaining data pipelines and analytics solutions that extract, transform, and load data from multiple source systems.
  • Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.
  • Experience managing data workflows in cloud environments such as AWS, Azure, or GCP.
  • Strong problem-solving skills with the ability to analyze complex data flow issues and implement sustainable solutions.
  • Working knowledge of SQL, Python, or scripting languages for process monitoring and automation.
  • Experience collaborating with data engineering, analytics, IT operations, and business teams in a matrixed organization.
  • Familiarity with data governance, metadata management, access control, and regulatory requirements (e.g., GDPR, HIPAA, SOX).
  • Excellent leadership, communication, and stakeholder engagement skills.
  • Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.
  • Strong analytical and problem-solving skills to address complex data challenges.
  • Effective communication and interpersonal skills to collaborate with cross-functional teams.
  • Data Engineering Management experience in Biotech/Life Sciences/Pharma
  • Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.
  • Excellent analytical and troubleshooting skills
  • Strong verbal and written communication skills
  • Ability to work effectively with global, virtual teams
  • High degree of initiative and self-motivation
  • Ability to manage multiple priorities successfully
  • Team-oriented, with a focus on achieving team goals
  • Strong presentation and public speaking skills

Locations

  • Hyderabad, India

Salary

Salary not disclosed

Estimated Salary Rangehigh confidence

80,000 - 120,000 USD / yearly

Source: xAI estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Experience managing a team of data engineers in biotech/pharma domain companies.intermediate
  • Experience in designing and maintaining data pipelines and analytics solutions that extract, transform, and load data from multiple source systems.intermediate
  • Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.intermediate
  • Experience managing data workflows in cloud environments such as AWS, Azure, or GCP.intermediate
  • Strong problem-solving skills with the ability to analyze complex data flow issues and implement sustainable solutions.intermediate
  • Working knowledge of SQL, Python, or scripting languages for process monitoring and automation.intermediate
  • Experience collaborating with data engineering, analytics, IT operations, and business teams in a matrixed organization.intermediate
  • Familiarity with data governance, metadata management, access control, and regulatory requirements (e.g., GDPR, HIPAA, SOX).intermediate
  • Excellent leadership, communication, and stakeholder engagement skills.intermediate
  • Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.intermediate
  • Strong analytical and problem-solving skills to address complex data challenges.intermediate
  • Effective communication and interpersonal skills to collaborate with cross-functional teams.intermediate
  • Data Engineering Management experience in Biotech/Life Sciences/Pharmaintermediate
  • Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.intermediate
  • Excellent analytical and troubleshooting skillsintermediate
  • Strong verbal and written communication skillsintermediate
  • Ability to work effectively with global, virtual teamsintermediate
  • High degree of initiative and self-motivationintermediate
  • Ability to manage multiple priorities successfullyintermediate
  • Team-oriented, with a focus on achieving team goalsintermediate
  • Strong presentation and public speaking skillsintermediate

Required Qualifications

  • 9 to 12 years of experience in Computer Science, IT or related field (experience)
  • AWS Certified Data Engineer preferred (experience)
  • Databricks Certificate preferred (experience)
  • Scaled Agile SAFe certification preferred (experience)

Responsibilities

  • Lead and manage the enterprise data operations team, responsible for data ingestion, processing, validation, quality control, and publishing to various downstream systems.
  • Define and implement standard operating procedures for data lifecycle management, ensuring accuracy, completeness, and integrity of critical data assets.
  • Oversee and continuously improve daily operational workflows, including scheduling, monitoring, and troubleshooting data jobs across cloud and on-premise environments.
  • Establish and track key data operations metrics (SLAs, throughput, latency, data quality, incident resolution) and drive continuous improvements.
  • Partner with data engineering and platform teams to optimize pipelines, support new data integrations, and ensure scalability and resilience of operational data flows.
  • Collaborate with data governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls.
  • Serve as the primary escalation point for data incidents and outages, ensuring rapid response and root cause analysis.
  • Build strong relationships with business and analytics teams to understand data consumption patterns, prioritize operational needs, and align with business objectives.
  • Drive adoption of best practices for documentation, metadata, lineage, and change management across data operations processes.
  • Mentor and develop a high-performing team of data operations analysts and leads.

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Amgen logo

Data Engineering Manager

Amgen

Data Engineering Manager

Amgen logo

Amgen

full-time

Posted: November 12, 2025

Number of Vacancies: 1

Job Description

ABOUT AMGENAmgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.ABOUT THE ROLERole Description:We are seeking a seasoned Engineering Manager (Data Engineering) to lead the end-to-end management of enterprise data assets

What you will do

  • Lead and manage the enterprise data operations team, responsible for data ingestion, processing, validation, quality control, and publishing to various downstream systems.
  • Define and implement standard operating procedures for data lifecycle management, ensuring accuracy, completeness, and integrity of critical data assets.
  • Oversee and continuously improve daily operational workflows, including scheduling, monitoring, and troubleshooting data jobs across cloud and on-premise environments.
  • Establish and track key data operations metrics (SLAs, throughput, latency, data quality, incident resolution) and drive continuous improvements.
  • Partner with data engineering and platform teams to optimize pipelines, support new data integrations, and ensure scalability and resilience of operational data flows.
  • Collaborate with data governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls.
  • Serve as the primary escalation point for data incidents and outages, ensuring rapid response and root cause analysis.
  • Build strong relationships with business and analytics teams to understand data consumption patterns, prioritize operational needs, and align with business objectives.
  • Drive adoption of best practices for documentation, metadata, lineage, and change management across data operations processes.
  • Mentor and develop a high-performing team of data operations analysts and leads.

What we expect of you

  • 9 to 12 years of experience in Computer Science, IT or related field
  • AWS Certified Data Engineer preferred
  • Databricks Certificate preferred
  • Scaled Agile SAFe certification preferred

Must-Have Skills

  • Experience managing a team of data engineers in biotech/pharma domain companies.
  • Experience in designing and maintaining data pipelines and analytics solutions that extract, transform, and load data from multiple source systems.
  • Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.
  • Experience managing data workflows in cloud environments such as AWS, Azure, or GCP.
  • Strong problem-solving skills with the ability to analyze complex data flow issues and implement sustainable solutions.
  • Working knowledge of SQL, Python, or scripting languages for process monitoring and automation.
  • Experience collaborating with data engineering, analytics, IT operations, and business teams in a matrixed organization.
  • Familiarity with data governance, metadata management, access control, and regulatory requirements (e.g., GDPR, HIPAA, SOX).
  • Excellent leadership, communication, and stakeholder engagement skills.
  • Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.
  • Strong analytical and problem-solving skills to address complex data challenges.
  • Effective communication and interpersonal skills to collaborate with cross-functional teams.
  • Data Engineering Management experience in Biotech/Life Sciences/Pharma
  • Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.
  • Excellent analytical and troubleshooting skills
  • Strong verbal and written communication skills
  • Ability to work effectively with global, virtual teams
  • High degree of initiative and self-motivation
  • Ability to manage multiple priorities successfully
  • Team-oriented, with a focus on achieving team goals
  • Strong presentation and public speaking skills

Locations

  • Hyderabad, India

Salary

Salary not disclosed

Estimated Salary Rangehigh confidence

80,000 - 120,000 USD / yearly

Source: xAI estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Experience managing a team of data engineers in biotech/pharma domain companies.intermediate
  • Experience in designing and maintaining data pipelines and analytics solutions that extract, transform, and load data from multiple source systems.intermediate
  • Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions.intermediate
  • Experience managing data workflows in cloud environments such as AWS, Azure, or GCP.intermediate
  • Strong problem-solving skills with the ability to analyze complex data flow issues and implement sustainable solutions.intermediate
  • Working knowledge of SQL, Python, or scripting languages for process monitoring and automation.intermediate
  • Experience collaborating with data engineering, analytics, IT operations, and business teams in a matrixed organization.intermediate
  • Familiarity with data governance, metadata management, access control, and regulatory requirements (e.g., GDPR, HIPAA, SOX).intermediate
  • Excellent leadership, communication, and stakeholder engagement skills.intermediate
  • Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools.intermediate
  • Strong analytical and problem-solving skills to address complex data challenges.intermediate
  • Effective communication and interpersonal skills to collaborate with cross-functional teams.intermediate
  • Data Engineering Management experience in Biotech/Life Sciences/Pharmaintermediate
  • Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc.intermediate
  • Excellent analytical and troubleshooting skillsintermediate
  • Strong verbal and written communication skillsintermediate
  • Ability to work effectively with global, virtual teamsintermediate
  • High degree of initiative and self-motivationintermediate
  • Ability to manage multiple priorities successfullyintermediate
  • Team-oriented, with a focus on achieving team goalsintermediate
  • Strong presentation and public speaking skillsintermediate

Required Qualifications

  • 9 to 12 years of experience in Computer Science, IT or related field (experience)
  • AWS Certified Data Engineer preferred (experience)
  • Databricks Certificate preferred (experience)
  • Scaled Agile SAFe certification preferred (experience)

Responsibilities

  • Lead and manage the enterprise data operations team, responsible for data ingestion, processing, validation, quality control, and publishing to various downstream systems.
  • Define and implement standard operating procedures for data lifecycle management, ensuring accuracy, completeness, and integrity of critical data assets.
  • Oversee and continuously improve daily operational workflows, including scheduling, monitoring, and troubleshooting data jobs across cloud and on-premise environments.
  • Establish and track key data operations metrics (SLAs, throughput, latency, data quality, incident resolution) and drive continuous improvements.
  • Partner with data engineering and platform teams to optimize pipelines, support new data integrations, and ensure scalability and resilience of operational data flows.
  • Collaborate with data governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls.
  • Serve as the primary escalation point for data incidents and outages, ensuring rapid response and root cause analysis.
  • Build strong relationships with business and analytics teams to understand data consumption patterns, prioritize operational needs, and align with business objectives.
  • Drive adoption of best practices for documentation, metadata, lineage, and change management across data operations processes.
  • Mentor and develop a high-performing team of data operations analysts and leads.

Target Your Resume for "Data Engineering Manager" , Amgen

Get personalized recommendations to optimize your resume specifically for Data Engineering Manager. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Data Engineering Manager" , Amgen

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Tags & Categories

Software EngineeringCloudFull StackInformation SystemsTechnology

Related Jobs You May Like

No related jobs found at the moment.