Job Title: AVP Data Engineering & Analytics (AWS)

Location: Gurugram Experience: 1015 Years Working Model: Hybrid

Immediate Joiners

Job Summary

We are looking for an experienced AVP Data Engineering & Analytics to lead the design, development, and delivery of scalable data platforms on AWS. This role requires a strong blend of hands-on data engineering expertise, leadership capabilities, and the ability to drive analytics-ready data solutions aligned with business needs.

The ideal candidate will have deep experience in building end-to-end data pipelines, working with modern data platforms like Databricks, and managing high-performing teams while engaging with global stakeholders.

Key Responsibilities

Lead and manage a team of 1025 data engineers and analysts
Design and build scalable ETL/ELT pipelines on AWS
Architect and implement data lake / lakehouse solutions using modern tools (e.g., Databricks, Delta Lake)
Ensure data quality, governance, and performance optimization across platforms
Collaborate with business stakeholders to translate requirements into data-driven solutions
Drive analytics enablement by preparing data for BI/ML use cases
Oversee end-to-end delivery from data ingestion to consumption
Mentor team members and drive best practices in data engineering
Work closely with cross-functional teams including data science, analytics, and business units

Must-Have Skills

Strong experience in Data Engineering (ETL/ELT, Data Warehousing)
Hands-on expertise in AWS (S3, Glue, Redshift, Lambda, EMR) or Azure.
Experience with Databricks / Delta Lake / Lakehouse architecture
Proficiency in Python, SQL, PySpark/Spark
Experience building large-scale, production-grade data pipelines
Proven team management experience (815 members)
Strong stakeholder management and communication skills

Good-to-Have

Exposure to GenAI / advanced analytics / ML workflows
Experience in Insurance domain
Knowledge of real-time data streaming (Kafka, Kinesis)
Understanding of CI/CD and DevOps practices for data platforms

Candidate Profile

1015 years of experience in Data Engineering / Analytics
Strong leadership experience at AVP / Lead level
Experience working with global clients and distributed teams
Ability to drive end-to-end ownership and delivery excellence

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