Lead, mentor, and develop an analytical engineering team focused on modelling standards, quality, and reusability.
Partner with the Principal Data Engineer to co-own end-to-end data delivery from foundational pipelines through to analytical data layers.
Shape career growth, training, and performance pathways that develop deep data craftsmanship within the team.
Foster a culture of collaboration between data engineering, governance, and analytics aligning priorities through shared objectives.
Define and embed best practices in data modelling, including standards for naming, documentation, and business logic representation.
Lead the design of subject-area models and data contracts that form the foundation for reporting, AI, and personalization.
Champion the evolution toward a semantic and governed analytical layer, ensuring traceability from raw data to business outcomes.
Partner with Product, Analytics, and Technology teams to translate business concepts into consistent, reusable data assets.
Maintain high standards of quality and simplicity in data design prioritizing clarity, trust, and performance over complexity.
Work hand-in-hand with the Principal Data Engineer to align platform evolution, modelling standards, and delivery governance.
Contribute to the Data & Analytics strategy and roadmap, ensuring analytical engineering practices scale with Collinsons data ambitions.
Represent analytical engineering in cross-functional forums, advocating for trusted data, lineage, and definition alignment.
Partner with Governance, Data Science, and BI teams to ensure analytical models meet the needs of both operational and strategic insight.
Knowledge, skills and experience required :
Essential :
Proven experience leading data or analytics engineering teams within a modern cloud data platform.
Deep understanding of data modelling principles, including dimensional and domain-driven design.
Experience shaping and governing semantic or analytical layers that underpin enterprise analytics.
Strong partnership skills particularly in co-leading design and delivery alongside technical peers (e.g., Principal Data Engineer).
Excellent communication and stakeholder management across business, data, and technology teams.
A passion for quality, maintainability, and clarity in analytical data design.
Desirable :
Exposure to data contracts, metadata management, or data governance frameworks.
Awareness of analytics enablement in AI-driven or personalization contexts.
Experience working with agile data teams balancing short-term delivery with long-term architecture.
Understanding of how analytical engineering integrates into data product, ML, and self-service strategies
(ref : hirist.tech)
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Engineering Manager • Mumbai
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