Lead AWS Data Engineer

Wissen Technology; Pune District; Hybrid; INR 2,400,000 - 4,200,000; Full time

Job summary

Wissen Technology in Pune Baner offers a hybrid role for a Lead Data Engineer (AWS + Big Data). You will design scalable data pipelines, mentor teams, and drive technical delivery across AWS-based data platforms, with mandatory Databricks exposure.

The ideal candidate has 8–14 years of data engineering experience, strong AWS, Spark, and Python/Java skills, plus CI/CD and data quality mindset. 2nd technical round is mandatory on-site in Pune.

Qualifications

• 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.

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.

Skills

AWS

Apache Spark

Databricks

HBase

Python

Java

SQL

ETL/ELT

Airflow

CI/CD

Git

Data Quality

Tools

Hadoop

Hive

Impala

Delta Lake

Snowflake

Kafka

Job description

Job Description Lead Data Engineer (AWS + Big Data)

Location:Baner, Pune - Hybrid
Experience:8–14 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 exposure is mandatory, while deep implementation experience in Databricks is not essential. 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 exposure (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 taken F2F from Pune, Wakad office.