Databricks Data Engineer

Mployee.me; Pune District; Hybrid; INR 3,500,000 - 6,000,000; Full time

Job summary

Mployee.me is hiring a Lead Data Engineer with strong hands-on experience in AWS-based Big Data platforms. You will design scalable data pipelines, own end-to-end delivery, and mentor engineering teams in a high-velocity, data-driven environment.

Databricks experience is mandatory. You will work with Spark/PySpark, HBase, Hive, and Kafka, along with S3, Glue, Lambda, IAM, and CloudWatch to build production-grade data solutions from Baner, Pune — Hybrid.

Qualifications

• 7–14 years of Data Engineering experience with AWS implementation.
• Experience leading technical delivery and mentoring engineering teams.
• Strong understanding of enterprise-scale data platforms and Big Data architectures.

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.

Skills

AWS

Databricks

Apache Spark

PySpark

Scala

HBase

Python

Java

SQL

Airflow

CI/CD

Job description

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 Engineerwith strong 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 experiencewill 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 modern 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.
• Strong 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 mandatory to be take F2F from, Wakad, Pune Office. (non negotiable)