Role Description: We are seeking a seasonedSeniorEngineering Manager(Data Engineering)tolead the end-to-end management of enterprise data assets and operational data workflows. This role is critical in ensuring the availability, quality, consistency, and timeliness of data across platforms and functions, supporting analytics, reporting, compliance, and digital transformation initiatives.As a senior leader in the data organization, you will oversee the day-to-day data operations, manage a team of data professionals, and drive process excellence in data intake, transformation, validation, and delivery. You will work closely with cross-functional teams including data engineering, analytics, IT, governance, and business stakeholders to align operational data capabilities with enterprise needs. Roles & 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 availability, 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. Functional Skills: Must-Have Skills: Experience managing a team of data engineers in biotech/pharmadomain companies. Experience in designing and maintainingdata 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 on Databricks 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, PySparkor 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 & observability 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. Good-to-Have Skills: Data Engineering Management experience in Biotech/Life Sciences/Pharma Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc. Education and Professional Certifications 12 to 15 years of experience in Computer Science, IT or related field Databricks Certificate preferred Scaled Agile SAFe certification preferred Experience in life sciences, healthcare, or other regulated industries with large-scale operational data environments. Familiarity with incident and change management processes (e.g., ITIL). Soft Skills: 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
