Role : Manager, Technology - Data, Analytics & AI
Job Location - Pune / Hyderabad (Hybrid).
Summary
In this exciting role, you would :
- Own the health, performance, and growth of a multidisciplinary Data, Analytics & AI domains and Engineering team (of Data / BI / ML Engineers and Analysts).
- Create the conditions for sustainable high performance : clear direction, strong collaboration, and career development.
- Enable the team to turn business problems into robust solutions and actionable insights while maturing practices, processes, and talent. Key Responsibilities
- Manage, coach, and develop a high-performing team (hiring, goal setting, feedback, growth planning).
- Partner with Tech Leadership, Product, and Business stakeholders to convert requirements into scalable data models, pipelines, semantic layers, and dashboards.
- Participate in the development of the technical vision for your team including contributing to the long-term roadmap.
- Drive data quality, governance, documentation, lineage, and metric definitions; reduce redundancy.
- Set and enforce engineering and analytics best practices (coding standards, version control, peer review, CI / CD, automated testing) while building an outcome / impact-based culture.
- Escalate and resolve complex technical and data issues; remove delivery blockers.
- Closely monitor status, identify and predict risks. Provide meaningful and actionable insights on progress.
- Manage project forecast and spending.
REQUIREMENTS AND QUALIFICATIONS
8+ years in data engineering / BI / analytics, including 3+ years directly managing teams. 2+ years of working experience with ML & Data Science is a plus.Bachelor’s in Computer Science / Applications, Engineering, Information Technology / Systems, or equivalent experience. Masters in any of these areas is a plus.Proven delivery of scalable data platforms and BI solutions in cloud (Azure preferred).Expertise with SQL, ELT / ETL patterns, dimensional & semantic modeling.Experience with Snowflake, Databricks, Data Factory, Oracle.Working knowledge of Python, Spark, Scala, and streaming technologies a huge plus.Strong BI development (Power BI and / or MicroStrategy) and performance tuning.Demonstrated governance : data quality frameworks, metadata, metric standardization.Solid grasp of software engineering practices (testing, code review, automation, DevOps).Excellent stakeholder management; able to translate between business and technical contexts.Track record of talent development and building collaborative, inclusive teams.Clear written and verbal communication; executive presentation capability.Typical Success Metrics
Team Health : Low regrettable attrition.Delivery Predictability : ≥80% of committed quarterly objectives delivered without quality regressions.Talent Growth : Documented progression for each team member; internal promotions / expanded scope.Operational Maturity : Reduction in unplanned urgent work and data incident frequency; improved cycle time.Stakeholder Trust : Positive satisfaction feedback (clarity, responsiveness, value realized).Adoption & Impact : Growth in usage of certified data products / dashboards and measurable business decisions influenced.