Senior Manager, Data Engineering - Devops
Posted
Summary
A people-leader role based in Chennai directing data engineering delivery — pipelines, data platforms, integration, and data quality — plus DevOps work: building CI/CD pipelines, managing Azure/AWS/GCP infrastructure as code with Terraform, and running monitoring/alerting with tools like Splunk and Datadog.
Job Summary
The Senior 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 Senior 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
• Bachelor's degree in Computer Science, Information Technology, Engineering, Design, Analytics, Business, or a related discipline
• 10 to 12 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
" Design, implement, and maintain CI/CD pipelines for build, test, and deployment automation
• Manage cloud infrastructure (Azure/AWS/GCP) using Infrastructure as Code (Terraform, ARM, CloudFormation)
• Automate environment provisioning, monitoring, and scaling
• Partner with development, QA, security, and release teams to improve deployment reliability
• Implement monitoring, alerting, and logging solutions (App Insights, Splunk, Datadog, Prometheus)
• Enforce security best practices, vulnerability remediation, and compliance controls
• Troubleshoot production issues and support incident response and root cause analysis" "
Secondary Skills:
• Lead, coach, develop, and motivate team members through clear goals, regular feedback, performance management, and development planning.
• Build and maintain effective relationships with business, technology, vendor, and leadership stakeholders across a matrix environment.
• Develop and maintain clear documentation for the data flows delivered by the engineering team.
• Communicate engineering delivery status, risks, trends, issues, and improvement recommendations to stakeholders and leadership.
• Promote data governance, security, privacy, access management, and compliance considerations in engineering processes.
• Foster a diverse, inclusive, collaborative, and service-oriented team culture. "