Manager Technology

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.