We're seeking a seasoned Senior Engineering Manager (Data Engineering) in Hyderabad to lead the end-to-end management of our enterprise data assets and operational data workflows. This is a critical leadership role focused on ensuring the availability, quality, consistency, and timeliness of data across all platforms and functions. You'll drive analytics, reporting, compliance, and digital transformation initiatives by overseeing daily data operations, managing a team of data professionals, and championing process excellence in data intake, transformation, validation, and delivery. Collaboration with cross-functional teams, including data engineering, analytics, IT, governance, and business stakeholders, will be key to aligning operational data capabilities with our 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 the 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 the 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/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 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, PySpark , 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 & 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, Marklogic, Neo4J, or Allegrograph, etc. Education and Professional Certifications 12 to 15 years of experience in Computer Science, IT, or a related field. Preferred : Databricks Certificate. Preferred : Scaled Agile SAFe certification. 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.