We are seeking a seasoned Engineering Manager to lead the end-to-end management of enterprise data assets and operational data workflows. This is a critical role focused on ensuring the availability, quality, consistency, and timeliness of data across platforms and functions. You will lead a team of data professionals and drive process excellence in data intake, transformation, validation, and delivery, supporting key initiatives such as analytics, reporting, and digital transformation.
Roles & Responsibilities
- Team Leadership & Data Operations: Lead and manage the enterprise data operations team, which is responsible for data ingestion, processing, validation, and publishing to various downstream systems. You will define and implement standard operating procedures for data lifecycle management and continuously improve daily operational workflows.
- Performance & Metrics: Establish and track key data operations metrics, such as SLAs, throughput, and data quality. You will serve as the primary escalation point for data incidents and outages, ensuring a rapid response and root cause analysis.
- Pipeline & Platform Optimization: Partner with data engineering and platform teams to optimize pipelines, support new data integrations, and ensure the scalability and resilience of operational data flows. You will have demonstrated hands-on experience with cloud platforms like AWS and the ability to architect cost-effective and scalable data solutions.
- Governance & Compliance: Collaborate with data governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls (e.g., GDPR, HIPAA, SOX). You will also drive the adoption of best practices for documentation, metadata, and change management.
- Cross-Functional Collaboration: Build strong relationships with business and analytics teams to understand data consumption patterns and prioritize operational needs. You will be expected to work effectively in a matrixed organization, mentoring and developing a high-performing team.
Qualifications
- 9 to 12 years of experience in Computer Science, IT, or a related field.
- Experience managing a team of data engineers, preferably in a biotech or pharma company.
- Experience in designing and maintaining data pipelines and analytics solutions on cloud platforms (AWS, Azure, or GCP).
- Strong working knowledge of SQL, Python, or other scripting languages for process monitoring and automation.
- Familiarity with data governance, metadata management, and regulatory requirements.
- Certifications such as AWS Certified Data Engineer, Databricks Certificate, or Scaled Agile SAFe are preferred.
Soft Skills
- Leadership: Excellent leadership, communication, and stakeholder engagement skills. You should have a high degree of initiative and self-motivation.
- Problem-Solving: Strong analytical, problem-solving, and troubleshooting skills, with the ability to analyze complex data flow issues and implement sustainable solutions.
- Collaboration: Effective communication and interpersonal skills to collaborate with cross-functional and global, virtual teams.
- Adaptability: The ability to manage multiple priorities successfully in a dynamic environment.
