Manager, IT - Data Engineering

Job DescriptionMANAGER, DATA ENGINEERING(b13)Job DescriptionRole overviewAs a Manager — Data Engineering, you will lead a cross-functional delivery team in building and maintaining the framework and platform capabilities that drive our data pipelines and analytics solutions. You will take design ownership of individual projects, run day-to-day team activities, and contribute to community-of-practice enablement and onboarding programs. Your team will work closely with stakeholders across the organisation to identify and mitigate data challenges and to create data assets that drive measurable business value.Primary responsibilitiesTeam leadership & deliveryLead and manage a team of data engineers, providing technical guidance and mentorship to ensure their growth and developmentTake design leadership over individual projects — own architecture decisions end-to-end, not just contributeTake charge of day-to-day team activities including scrum ceremonies, sprint planning, and backlog managementOversee the development and operation of modern data engineering solutions, including data ingestion, processing, integration, and governanceCollaborate with stakeholders to identify business needs and develop solutions that meet those needsCommunity of practice contributionDevelop and maintain shared frameworks for data engineering; contributions should reflect design for broader organisational scope, not just the immediate teamContribute to the onboarding of new data engineers, analysts, product owners, and other team members joining the projectContribute to community-of-practice enablement programs — including internal upskilling and certification, training frameworks, and knowledge-sharing initiativesAct as a data owner and functional subject matter expert for assigned areas, supporting data product certification and lineage maturityPlatform & operationsEnsure platform stability and operational SLAs; drive reduction in operational noise and manual interventionExtend DevOps capabilities for deploying and operating data solutionsWork closely with product owners and stakeholders to identify and mitigate potential data challengesSupport the adoption of AI and LLM-based tooling to improve engineering efficiency and data qualityQualificationsEducationBachelor's degree or higher in Computer Science, Statistics, Business, Information Technology, or a related fieldExperience5+ years of experience in data engineering or a related discipline, with at least 2 years in a technical lead or team lead capacityProven track record delivering and supporting software and data engineering capabilities in a fast-paced, dynamic environmentExperience contributing to shared frameworks within the data domain, and creating data assets used in mission-critical applicationsTechnical skillsIntermediate data design skills — data modelling, schema design, and pipeline architecture for enterprise-scale solutionsCore Python proficiency — including object-oriented programming, reusable library design, and clean scalable code; not just ad hoc scriptingAdvanced SQL — window functions, query optimisation, and complex transformation logic beyond basic CRUD operations; experience with dbt is a plusIntermediate DevOps and cloud (Azure, AWS, or GCP) — including CI/CD pipeline ownership, deployment practices, and cloud cost awarenessExperience with Agile methodologies; hands-on experience running scrum ceremoniesExperience with automated testing and data testing frameworks — able to design and enforce test coverage across pipelines and data assetsDomain expertise5+ years building enterprise data solutions with a proven track record delivering high-quality pipelines and analytics productsFamiliarity with modern orchestration and transformation tooling — Dagster, dbt, and Snowflake experience strongly preferredUnderstanding of data warehousing concepts and architecture patterns such as medallion architecture and dimensional modellingAwareness of data product concepts including lineage, certification, and operational telemetryExperience implementing data quality frameworks — including validation, profiling, and monitoring — to ensure integrity and consistency across data systemsExperience working in environments where data engineering capabilities are shared as platform services, not built in isolationIndividual skillsStrong collaborator and team player, with the ability to work effectively with business stakeholders and cross-functional teamsStrong analytical thinker — able to troubleshoot complex pipeline issues, optimise performance, and identify improvement opportunities across data systemsClear point of view on data engineering best practices — and the ability to bring others along, not just hold the opinionEffective communicator who can translate technical decisions into business languageMindsets and behavioursEmbraces change and is passionate about driving innovation and continuous improvementBelieves in a non-hierarchical culture of collaboration, transparency, safety, and trustNot afraid to take risks and try new approaches; willing to learn from failure and use it to drive growthInvested in the growth of others — sees enabling teammates as part of their own successLocation(s)Bengaluru - Brookfield GCC Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes.