Job Description Lead Data Engineer (AWS + Big Data)

Location: Baner, Pune - Hybrid
Experience: 7–14 Years

Role Overview

We are looking for a Lead Data Engineer with solid hands-on expertise in AWS-based Big Data platforms. The ideal candidate shouldhave extensive implementation experience in designing and building scalable data pipelines, mentoring engineering teams, and driving technical delivery. Databricks experience is mandatory. Candidates with HBase experience will be preferred.

Key Responsibilities
Design, develop, and maintain scalable data pipelines and ETL/ELT solutions on AWS.
Build and optimize Big Data applications using Spark/PySpark, HBase, Hive, Kafka, and related technologies.
Work with AWS services such as S3, Glue, Lambda, IAM, and CloudWatch for cloud-native data engineering.
Lead technical implementation, mentor engineers, conduct code reviews, and drive engineering best practices.
Ensure data quality, performance optimization, CI/CD adoption, and production support.

Required Skills
Strong hands-on experience with AWS (S3, Glue, Lambda, IAM,



CloudWatch)
Apache Spark (PySpark/Scala) and Big Data ecosystem
Databricks experience (mandatory)
HBase (strongly preferred)
Python or Java, Advanced SQL
ETL/ELT development and Data Warehousing concepts
Apache Airflow or similar orchestration tools
Git, CI/CD, Performance Tuning, and Data Quality

Good to Have
Kafka / Spark Structured Streaming
Hive, Impala, Hadoop ecosystem
Delta Lake / Lakehouse concepts
Snowflake or other up-to-date cloud data platforms

Experience Required
8–14 years of Data Engineering experience with strong AWS implementation expertise.
Proven experience leading technical delivery and mentoring engineering teams.
Robust understanding of enterprise-scale data platforms and Big Data architectures.
Ability to collaborate with architects, stakeholders, and cross-functional teams to deliver scalable solutions.

NOTE: 2nd Technical round is mandat

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