Manager, Data Engineering
DU TECH Chennai, Tamil Nadu, India
IT Services and IT Consulting · 201-500 employees
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About the role
Lead data engineering delivery and operational performance across pipelines, platforms, integrations, data quality, and governed data products. Develop the team, translate business priorities into measurable plans, and uphold quality, security, privacy, compliance, and operational standards.
What they look for
Requirements
Requires a bachelor's degree in a relevant discipline and 4–9 years of relevant experience, with experience in data engineering, team or delivery leadership, and cross-functional collaboration. Candidates should know SQL, Python or similar languages, ETL/ELT, cloud data platforms, data modeling, orchestration, and data quality; a related master's degree and relevant certifications are preferred.
Full description
Job Summary - Job Description (Internal) Job Summary - Job Advert (External)
The Manager, Data Engineering leads data engineering delivery and operational performance across data pipelines, data platforms, integration, data quality, and governed data products. This people-leader role translates business and product priorities into plans, establishes quality and governance expectations, manages risks and dependencies, and develops a high-performing team that delivers measurable outcomes. DU Tech is looking for a Manager, Data Engineering to lead data engineering capabilities across data pipelines, data platforms, integration, data quality, and governed data products. This role combines people leadership, delivery accountability, stakeholder partnership, and disciplined execution to deliver reliable, scalable, secure, and customer-focused outcomes.
Job Responsibilities
Delivery & Execution
- Lead planning, delivery, and operational performance for data engineering.
- Guide a team responsible for data pipelines, data platforms, integration, data quality, and governed data products.
- Translate priorities into roadmaps, plans, backlogs, and measurable outcomes.
- Reinforce quality, architecture, security, privacy, compliance, and operational standards.
- Manage capacity, delivery risks, dependencies, budgets, and vendors as applicable.
- Use metrics to improve quality, speed, reliability, cost, and stakeholder value.
Support & Enablement
- Lead, coach, and develop team members; support hiring, performance, and talent processes.
- Build strong partnerships across business, product, architecture, security, data, and technology teams.
- Communicate priorities, progress, risks, and decisions clearly.
- Create an inclusive, accountable, and high-performing team environment.
Requirements
Education & Experience Type of Experience*
- Bachelor's degree in Computer Science, Information Technology, Engineering, Design, Analytics, Business, or a related discipline
- 4 to 9 years of relevant experience in data engineering or a closely related discipline
- Experience with data pipelines, data platforms, integration, data quality, and governed data products
- Experience leading teams, workstreams, programs, or technology delivery in a complex organization
- Knowledge of SQL, Python or similar languages, ETL/ELT, cloud data platforms, data modeling, orchestration, and data quality
- Experience collaborating across business and technology teams
- Strong analytical, problem-solving, written, and verbal communication skills
Preferred Qualifications & Interests (PQIs)
- Master's degree in a related technical or business field is preferred
- Advanced knowledge of SQL, Python or similar languages, ETL/ELT, cloud data platforms, data modeling, orchestration, and data quality
- Experience with enterprise-scale cloud, data, digital, retail, pharmacy, healthcare, or customer technology environments
- Experience working with global teams, managed service partners, or distributed delivery models
- Relevant industry, cloud, agile, product, architecture, data, security, design, or technology certifications are preferred
Key Primary Skills
"• Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
- 3+ years of experience in data engineering
- Strong SQL, PySpark/Scala Spark development experience.
- Design ETL/ELT pipelines using PySpark, SQL, Spark Structred Streaming, and Databricks workflows - Lakeflow.
- Capable of developing streaming data pipelines using PySpark APIs / Scala Spark APIs (version 3+) , Lakeflow concepts, Unity Catalog features
- Capable of coding with or without AI assistants
- Experience designing and supporting data pipelines; working in cross-functional or matrix organizations.
- Ability to communicate technical concepts effectively.
- Willingness to travel up to 10% as needed. "
Secondary Skills
"• SQL
- Python / Scala
- ETL Development
- Databricks
- Azure Cloud Technologies
- Data Modeling
- Data Warehousing
- Big Data Platforms
- REST APIs "
