Staff Software Engineer

About Business Unit:

The Product team forms the crux of our powerful platforms and helps connect millions of customers worldwide with the brands that matter most to them. This team of innovative problem solvers develops and builds products that position Epsilon as a differentiator, encouraging an open and balanced marketplace built on respect for individuals, where every brand interaction holds value. Our full-cycle product engineering and data teams chart the future and set new benchmarks for our products, by using industry standard methodologies and sophisticated capabilities in data, machine learning, and artificial intelligence. Driven by a passion for delivering smart end-to-end solutions, this team plays a key role in Epsilon's success story.

Why are we looking for you

At Epsilon, we run on our people's ideas. It's how we solve problems and exceed expectations. Our team is now growing, and we are on the lookout for skilled individuals who always rset a higher standardby constantly challenging themselves and are experts in building customized solutions in the digital marketing space. So, are you someone who wants to work with pioneering technology and enable marketers to create data-driven, omnichannel consumer experiences through data platforms Then you could be exactly who we are looking for. Apply today and be part of a creative, innovative, and talented team that's not afraid to push boundaries or take risks.

What will you enjoy in this role

As a Staff Software Engineer in the Cleanroom team, you will operate at a platform and organization-wide level, driving architecture, technical strategy, and execution for mission-critical data systems. You will define engineering architecture and standards, influence long-term platform direction, mentor senior engineers, and ensure the Cleanroom platform scales securely and reliably to support sustained business growth.

Click here to view how Epsilon transforms marketing with 1 View, 1 Vision and 1 Voice.

Responsibilities

• Architect, design, and deliver large-scale cloud-native data platforms primarily on AWS, with exposure to Azure and GCP, using Databricks and distributed processing frameworks to build highly scalable and resilient systems.
• Work hands-on across the technology stack - including Python, PySpark, Apache Spark, Databricks, AWS services, event-driven architectures, and SQL/NoSQL databases - to solve complex engineering challenges and maintain platform excellence.
• Lead organization-wide technical initiatives focused on performance optimization, scalability, reliability, security, governance, and cost efficiency.
• Review and influence critical architectural decisions across teams while establishing engineering best practices and architectural governance standards.
• 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.
• Mentor and guide senior and junior engineers, fostering a culture of innovation, accountability, collaboration, and technical excellence.

Qualifications

• B.E/B.Tech/M.Tech/MCA in Computer Science, Information Technology or a related field.
• 10-13 years of strong software engineering experience, with significant expertise in large-scale data engineering and distributed systems architecture.
• Solid expertise 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 and managing massive-scale datasets for analytics and business intelligence workloads.
• Strong experience with AWS services such as S3, Glue, Redshift, EMR, Athena, Lambda, and EventBridge for building scalable and reliable cloud-native data platforms.
• Experience with real-time and near real-time streaming technologies including Kafka, AWS Kinesis, SQS, and RabbitMQ.
• Strong understanding of both relational and NoSQL databases, including PostgreSQL, SQL Server, Aurora, RDS, MongoDB, and DynamoDB.
• Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform or Ansible.
• Strong understanding of CI/CD and DevOps practices using tools such as Jenkins, Github/GitLab, Bitbucket, GoCD and automated deployment pipelines.
• Proven ability to influence technical direction, drive multi-functional initiatives, and lead complex engineering programs at scale.
• Exposure to Generative AI technologies including LLMs, RAG architectures, and Agentic AI systems, with experience designing and deploying AI driven solutions.

Nice to have:

• AWS and Databricks certifications and experience with Azure / Google Cloud Platform (GCP)
• Working knowledge of TypeScript, Node.Js and UX design & development.
• Experience building data platforms in privacy-safe or cleanroom environments.