Dir , Data Engineering

Job Description

What will you do in this role:

• Partner with colleagues in scientific data product line and stakeholders to understand the data priorities in support of research outcomes
• Partner with engineering teams in scientific data product line to understand and influence architectural choices and talent needs
• Define/Influence engineering squad configuration in collaboration with product manager and product tech lead to support roadmap objectives for products in Scientific Data Product Line
• Provide leadership to engineering squads in Hyderabad Tech Center (HTC) to design/engineer and implement data product features in support of research
• Define and implement data engineering strategies that align with organizational goals and data governance standards.
• Connect with external partners and thought leaders to stay current on the latest technologies and trends in Data Engineering.

• Evaluate and introduce new technologies, tools, and frameworks that enhance productivity and data quality.
• Conduct regular 1:1s, performance reviews, career development planning, and succession planning.

• In collaboration with Scientific Data product Line leader and product line technical leader, understand current and future engineering talent needs

• Drive recruitment, onboarding, and retention of top data engineering talent.
• Develop and execute a learning roadmap for the engineering team in Tech Center (training, certifications, communities of practice, internal tech talks).
• Foster a culture of learning, innovation, psychological safety, and knowledge sharing.

• Understand the purpose of our company and role of research and research IT in support of this purpose
• Be an ambassador to help the team and broader HTC community understand and internalize this purpose
• Work with other engineering leaders in HTC to develop and participate in a community to learn engineering practices from each other
• Leverage enterprise engineering tools and processes and be an advocate for them in the team and beyond. Actively provide feedback to enterprise teams to evolve these tools and processes in support of research engineering needs

What Should you have:

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Mathematics, or related field; or equivalent experience.
• Typically, 10+ years of experience in data engineering or related roles, with 5+ years in a leadership, lead engineer, or chapter/people lead capacity.
• Proven track record building and maintaining large-scale data platforms and pipelines in complex enterprise environments.

Technical Skills

• Strong hands-on experience with modern data engineering technologies, such as:
  • Programming: Python, Java, SQL
  • Data processing: Spark, Databricks, dBt, Matillion
  • Data warehousing / Lakehouse: Delta Lake, Redshift, Neptune
  • Cloud platforms: AWS (preferred)/ Azure
  • Streaming: Kafka, Kinesis, Pub/Sub, Event Hubs, etc.
• Solid understanding of:
  • ETL/ELT concepts
  • Data quality, metadata management, and observability
  • CI/CD, Infrastructure as Code, and containerization (e.g., GitHub/GitLab CI, Jenkins, Terraform, Docker, Kubernetes)
  • Security, privacy, and compliance concepts (e.g., RBAC, encryption, PII handling).

Leadership & Soft Skills

• Demonstrated ability to lead and grow technical teams and communities in a product team environment.
• Strong coaching and mentoring skills; able to develop both technical and behavioral capabilities.
• Strategic mindset with the ability to balance long-term architecture with short-term delivery needs.
• Excellent communication and influencing skills, with experience of engaging senior stakeholders.
• Comfortable working in agile environments (Scrum/Kanban) and applying product centric ways of working.

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