Senior Software Engineer

Responsibilities

• Deliver large‑scale cloud‑native data platforms primarily on AWS leveraging Databricks and distributed processing frameworks to build highly scalable and resilient systems.
• Work hands‑on across the technology stack—including Python, Java, PySpark, Apache Spark, Databricks, AWS services, event‑driven architectures, and SQL/No
  
  SQL databases—to solve complex engineering challenges and maintain platform excellence.
• Partner closely with global engineering, product management, architecture, and business stakeholders to align technical solutions with strategic business objectives.
• Own the end‑to‑end software development lifecycle, including requirements gathering, solution design, development, deployment, observability, and documentation.
• Design and develop reusable, maintainable and scalable components and actively participate in architecture discussions, technical design reviews, and code reviews.
• Mentor and guide junior engineers, fostering a culture of innovation, accountability, collaboration, and technical excellence.

• B.E/B.Tech/M.Tech/MCA in Computer Science, Information Technology or a related field.
• 5‑8 years of strong software engineering experience, with significant expertise in large‑scale data engineering and distributed systems architecture.
• Experience in Data Warehousing, Data Lakes, Delta Lake architecture, and modern big data ecosystem designs.
• Deep hands‑on expertise in Databricks, Python, PySpark, and Apache Spark, with proven experience building high‑performance distributed data processing solutions.
• Strong experience with AWS services such as S3, Lambda, API Gateway, and Event Bridge for building scalable, reliable, cloud‑native data.
• Experience with messaging technologies such as Kafka, along with strong expertise in relational and No
  
  SQL databases including SQL Server and MongoDB.
• Experience implementing robust testing strategies, including unit, integration, and regression testing, while adhering to engineering best practices.
• Strong understanding of CI/CD and Dev Ops practices using tools such as Jenkins, Git Hub, Git Lab, Bitbucket, and automated deployment pipelines. Hands‑on experience with Infrastructure as Code tools such as Terraform and Ansible.
• Strong critical thinking and analytical skills, with the ability to diagnose, troubleshoot, and solve complex technical problems effectively.

• AWS and Databricks certifications.
• Experience working with Azure and/or Google Cloud Platform (GCP).
• Exposure to Generative AI technologies including LLMs, RAG architectures, and Agentic AI systems, with experience designing and deploying AI‑driven solutions.

Compensation Range: USD $ - USD $/Annually.

Epsilon is an Equal Opportunity Employer. Epsilon’s policy is not to discriminate against any applicant or employee based on actual or perceived race, age, sex or gender (including pregnancy), marital status, national origin, ancestry, citizenship status, mental or physical disability, religion, creed, color, sexual orientation, gender identity or expression (including transgender status), veteran status, genetic information, or any other characteristic protected by applicable federal, state or local law.

Epsilon also prohibits harassment of applicants and employees based on any of these protected categories. Epsilon will provide accommodations to applicants needing accommodations to complete the application process. Please reach out to  to request an accommodation.