Lead Data Operations Engineer

Lead Data Operations engineer, Precision Medicine Team

Career Category

Engineering

Job Description

ABOUT AMGEN

Amgen 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.

Role Description

The Precision Medicine Team builds and operates enterprise-scale data platforms that enable data search, cohort building, and knowledge discovery for Amgen’s scientific community. These platforms provide governed, secure access to critical human datasets, studies, and scientific knowledge, accelerating data-driven research and innovation.

We are seeking a Lead Operations Data Engineer to provide technical and operational leadership for GxP-compliant data platforms built on Databricks and AWS. This role is responsible for ensuring platform reliability, operational excellence, and continuous improvement across production data pipelines and services.

The ideal candidate combines deep hands-on data engineering expertise with ownership of operational processes, acting as a technical lead and escalation point while partnering closely with platform engineering, DevOps, quality, and compliance teams.

Roles & Responsibilities

Data Platform Operations & Support

• Own operational support for enterprise data pipelines and data platforms, including monitoring, troubleshooting, incident response, and root-cause analysis.
• Ensure high availability, reliability, and performance of Databricks- and AWS-based data solutions.
• Support GxP-compliant data environments, ensuring adherence to validation, audit readiness, and data integrity requirements.
• Execute and improve runbooks, SOPs, and operational procedures for data platform support.

Team Leadership & Operations

• Lead, coach, and develop the Data Management Support Operations team
• Define roles, responsibilities, and on-call/support coverage models
• Establish performance expectations, KPIs, and career development plans
• Foster a culture of accountability, continuous improvement, and customer focus

Support & Service Management

• Own operational support for data platforms (e.g., data warehouses, data lakes, ETL/ELT pipelines, analytics tools)
• Oversee incident, problem, and request management processes
• Ensure SLAs, OLAs, and response/resolution targets are met
• Act as escalation point for complex or high-impact issues
• Perform root cause analysis (RCA) for recurring incidents and partner with engineering teams to implement permanent fixes.
• Ensure consistent and high‑quality support execution across shifts, regions, and platforms.
• Coach team members on troubleshooting skills, ServiceNow best practices, and business communication.

Process & Continuous Improvement

• Design and improve support processes aligned with ITIL or similar frameworks
• Identify recurring issues and drive root cause analysis and remediation
• Partner with engineering teams to transition new solutions into support (operational readiness)
• Drive automation and self-service capabilities to reduce manual effort

Governance, Risk & Compliance

• Ensure support operations comply with data governance, security, and regulatory requirements
• Maintain documentation, runbooks, and audit-ready operational procedures
• Support validation, change management, and access control processes where required

Stakeholder Collaboration

• Serve as primary interface between support operations and data/platform owners
• Communicate operational health, risks, and improvement initiatives to leadership
• Partner with product, engineering, and business teams to align support priorities with business needs

Good-to-Have Skills

• Experience in Biotech or Pharma data platforms
• Exposure to Data Fabric or Data Mesh architectures
• Experience supporting APIs or data services for downstream consumers
• Knowledge of SQL/NoSQL databases, and performance tuning for OLAP/OLTP workloads
• Familiarity with CI/CD tools (e.g., Jenkins, Git) and infrastructure automation
• Experience with ITIL-aligned operations or service management practices

Education & Certifications

• Master’s degree with 6+ years of experience in Computer Science, IT, or related field

OR

• Bachelor’s degree with 8–10 years of relevant experience

Preferred technical skills:

• Familiarity with cloud data platforms (e.g., data lakes, data warehouses).
• Experience supporting ETL/ELT tools, orchestration frameworks, and data quality tools.
• Understanding of monitoring, alerting, and on‑call operations in data platforms.

Soft Skills

• Strong operational mindset with attention to detail
• Excellent analytical and troubleshooting abilities
• Clear verbal and written communication skills
• Ability to work effectively with global, distributed teams
• Comfortable managing multiple priorities in a production environment
• Team-oriented with a strong sense of ownership and accountability

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Experience Level

Senior Level