Senior Data Platform Engineer (AWS/Databricks)

Publicis Groupe ANZ; Wakefield (MA); On-site; USD 102,000 - 190,000; Full time

Benefits offered by this job

Medical coverage

Dental

Vision

Disability

401(k)

Paid time off

Job summary

Epsilon is seeking a Senior Software Engineer for the Cleanroom team to drive delivery of large-scale data platforms on cloud-native infrastructure. You will define engineering standards, implement best practices, and mentor junior engineers while ensuring scalable, secure, and reliable data solutions.

You will work hands-on with Python, PySpark, Spark, Databricks, and AWS services, collaborating with product and architecture teams to meet strategic goals and deliver high-quality, observable

Qualifications

• B.E./B.Tech./M.Tech./MCA in Computer Science, Information Technology or a related field.
• 5-8 years of strong software engineering experience in data engineering and distributed systems.
• Experience with Data Warehousing, Data Lakes, Delta Lake architecture and big data design.
• Deep hands-on Databricks, Python, PySpark and Apache Spark expertise.

Responsibilities

• Deliver large-scale cloud-native data platforms on AWS using Databricks.
• Work across Python, PySpark, Spark, Databricks, AWS services and SQL/NoSQL databases.
• Collaborate with global teams to align solutions with business objectives.
• Own end-to-end SDLC from requirements to deployment and observability.
• Design reusable components and participate in architecture discussions and code reviews.
• Mentor junior engineers and foster innovation and accountability.

Skills

Python

PySpark

Apache Spark

Databricks

AWS

Kafka

RabbitMQ

SQL

NoSQL

CI/CD

DevOps

Jenkins

GitHub

GitLab

Bitbucket

Education

B.E./B.Tech./M.Tech./MCA in Computer Science, Information Technology or a related field

Tools

Databricks

Python

PySpark

Apache Spark

AWS

S3

Glue

Athena

Lambda

Kafka

RabbitMQ

SQL Server

MongoDB

Job description

Epsilon is seeking a Senior Software Engineer for the Cleanroom team to drive delivery of large-scale data platforms on cloud-native infrastructure. You will define engineering standards, implement best practices, and mentor junior engineers while ensuring scalable, secure, and reliable data solutions.

You will work hands-on with Python, PySpark, Spark, Databricks, and AWS services, collaborating with product and architecture teams to meet strategic goals and deliver high-quality, observable