Job Description MANAGER DATA ENGINEERING b13 Job Description Role overview As a Manager Data Engineering you will lead a crossfunctional 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 daytoday team activities and contribute to communityofpractice 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 responsibilities Team leadership delivery Lead and manage a team of data engineers providing technical guidance and mentorship to ensure their growth and development Take design leadership over individual projects own architecture decisions endtoend not just contribute Take charge of daytoday team activities including scrum ceremonies sprint planning and backlog management Oversee the development and operation of up-to-date data engineering solutions including data ingestion processing integration and governance Collaborate with stakeholders to identify business needs and develop solutions that meet those needs Community of practice contribution Develop and maintain shared frameworks for data engineering contributions should reflect design for broader organisational scope not just the immediate team Contribute to the onboarding of new data engineers analysts product owners and other team members joining the project Contribute to communityofpractice enablement programs including internal upskilling and certification training frameworks and knowledgesharing initiatives Act as a data owner and functional subject matter expert for assigned areas supporting data product certification and lineage maturity Platform operations Ensure platform stability and operational SLAs drive reduction in operational noise and manual intervention Extend DevOps capabilities for deploying and operating data solutions Work closely with product owners and stakeholders to identify and mitigate potential data challenges Support the adoption of AI and LLMbased tooling to improve engineering efficiency and data quality Qualifications Education Bachelors degree or higher in Computer Science Statistics Business Information Technology or a related field Experience 5 years of experience in data engineering or a related discipline with at least 2 years in a technical lead or team lead capacity Proven track record delivering and supporting software and data engineering capabilities in a fastpaced dynamic environment Experience contributing to shared frameworks within the data domain and creating data assets used in missioncritical applications Technical skills Intermediate data design skills data modelling schema design and pipeline architecture for enterprisescale solutions Core Python proficiency including objectoriented programming reusable library design and clean scalable code not just ad hoc scripting Advanced SQL window functions query optimisation and complex transformation logic beyond basic CRUD operations experience with dbt is a plus Intermediate DevOps and cloud Azure AWS or GCP including CI CD pipeline ownership deployment practices and cloud cost awareness Experience with Agile methodologies handson experience running scrum ceremonies Experience with automated testing and data testing frameworks able to design and enforce test coverage across pipelines and data assets Domain expertise 5 years building enterprise data solutions with a proven track record delivering highquality pipelines and analytics products Familiarity with modern orchestration and transformation tooling Dagster dbt and Snowflake experience strongly preferred Understanding of data warehousing concepts and architecture patterns such as medallion architecture and dimensional modelling Awareness of data product concepts including lineage certification and operational telemetry Experience implementing data quality frameworks including validation profiling and monitoring to ensure integrity and consistency across data systems Experience working in environments where data engineering capabilities are shared as platform services not built in isolation Individual skills Solid collaborator and team player with the ability to work effectively with business stakeholders and crossfunctional teams Strong analytical thinker able to troubleshoot complex pipeline issues optimise performance and identify improvement opportunities across data systems Transparent point of view on data engineering best practices and the ability to bring others along not just hold the opinion Effective communicator who can translate technical decisions into business language Mindsets and behaviours Embraces change and is passionate about driving innovation and experiance 24 skill data engineering team leadership

📌 Manager IT Data Engineering (India)
🏢 The Kraft Heinz
📍 India