Senior Manager, Data Engineering & DataOps

Overview

Lead Data Engineering and DataOps as an anchor leader for operational excellence across the data platform. Own the DataOps strategy for the group and lead data engineers through the Build + Run + Support lifecycle.

What you'll do

• Own the DataOps strategy and operational roadmap for the group, covering pipeline reliability, monitoring, incident management, and continuous delivery practices.
• Manage allocation and day-to-day direction of data engineering resources focused on operational delivery across cross-functional teams.
• Establish and enforce DataOps standards including SLAs, SLOs, alerting thresholds, data quality checks, and observability frameworks.
• Lead incident response culture by defining escalation paths, conducting post-mortems, and driving systemic remediation to reduce recurring pipeline failures.
• Drive CI/CD adoption across data pipelines, ensuring automated testing, deployment, and rollback capabilities are standard practice.
• Hold engineering team members accountable for delivery tracking, operational transparency, and timely escalation using shared metrics and evidence.
• Conduct and govern code and pipeline reviews to ensure consistency, resilience, and maintainability across all teams.
• Manage a backlog of platform and operational improvements to enhance pipeline efficiency, security, and cost optimization on the cloud analytics platform.
• Oversee data quality operations by implementing and maintaining data quality frameworks, managing data contracts, and ensuring downstream trust in data assets.
• Collaborate with product owners, stakeholders, and data consumers to identify operational risks and proactively mitigate data reliability issues.
• Lead hiring and onboarding for data engineering roles within the group, with a focus on operational and platform engineering skills.
• Design and deliver technical training programs focused on DataOps practices, tooling, and operational mindset for data engineers.

What you'll need

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• 6+ years of experience in data engineering, with significant focus on data operations, platform reliability, or DevOps/DataOps practices.
• Proven experience leading teams and managing delivery in a fast-paced, cross-functional environment.
• Strong Python programming skills applied to pipeline development, automation, and operational tooling.
• Expert SQL development with deep understanding of query performance and data reliability patterns.
• Expertise with automated data testing frameworks, including Great Expectations, dbt, and pytest, and CI/CD tooling, including Azure DevOps and GitHub Actions.
• Proven experience with data warehousing platforms, such as Snowflake and BigQuery, and their operational management.
• Solid experience with major cloud platforms and infrastructure, including cost management and optimization.
• Strong knowledge of pipeline orchestration tools, such as Airflow, Azure Data Factory, and Prefect, and monitoring/alerting frameworks.
• Familiarity with observability tooling, such as Datadog and Azure Monitor, applied to data pipeline health.
• Familiarity with BI tools, including Tableau, Power BI, and Looker, as downstream consumers of operational data products.
• 6+ years of experience delivering enterprise-level data solutions in production environments.
• Demonstrated experience owning and improving the operational health of large-scale data platforms.
• Proven ability to implement DataOps and DevOps practices, including CI/CD, IaC, automated testing, and monitoring, in the data domain.
• Experience managing data quality operations and enforcing data contracts across multiple consuming teams.
• Experience with Agile and Kanban methodologies applied to operations and platform work.
• Experience leading and developing cross-functional data engineering teams.
• Track record of reducing pipeline failure rates and improving mean time to resolution (MTTR) through systemic improvements.
• Experience collaborating with platform, cloud infrastructure, and security teams to operationalize data pipelines at scale.
• Excellent communication skills, with the ability to translate operational risks and metrics into business impact for non-technical stakeholders.
• Strong analytical and problem-solving skills, with a bias toward root cause resolution over workarounds.
• Proven ability to build operational processes that scale across teams and geographies.
• Passion for operational excellence and the reliability engineering mindset applied to data.
• Continuous learner with agility across both technical tooling and business process domains.
• Self-starter who thrives in environments that reward initiative, ownership, and entrepreneurial thinking.
• Belief in a culture of transparency, psychological safety, and evidence-based decision-making.
• Commitment to building team capability—not just solving problems individually, but raising the floor for the whole group.

Nice to have

• Master's degree.
• Experience with Azure cloud platforms and infrastructure.

Details

• Location: Bengaluru - Brookfield GCC.