Staff Engineer
First seen by Alion on Oct 24, 2026.
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.
We seek Staff Software Engineers with experience building and scaling services in on-premises and cloud environments. As a Lead/Principal Engineer in the Epsilon Attribution/Forecasting Product Development team, you will design, implement, and optimise data processing solutions using Scala, Spark, and Hadoop. Collaborate with cross-functional teams to deploy big data solutions on our on-premises and cloud infrastructure, along with building, scheduling and maintaining workflows. Perform data integration and transformation, troubleshoot issues, Document processes, communicate technical concepts clearly, and continuously enhance our attribution engine/forecasting engine. Strong written and verbal communication skills (in English) are required to facilitate work across multiple countries and time zones. Good understanding of Agile Methodologies - SCRUM.
Requirements:
- Strong experience (12+ years) in Python/Scala programming language and extensive experience with Apache Spark for big data processing for developing and supporting both on-prem and cloud operations, especially on AWS and as needed with GCP cloud.
- Using Python to develop infrastructure modules.
- Hence, hands-on experience with Python.
- In-depth understanding of the Hadoop ecosystem, including HDFS, YARN, and MapReduce.
- Solid grasp of database systems and SQL for writing efficient SQLs(RDBMS/Warehouse) to handle TBS of data.
- Experience in building, scheduling and maintaining DAG workflows.
- Familiarity with data warehousing concepts and technologies.
- End-to-end ownership with definition, development, and documentation of software's objectives, business requirements, deliverables, and specifications in collaboration with partners.
- Experience in working on GIT (or equivalent source control).
- Understand Unit and integration test frameworks.
- Must have the ability to collaborate with stakeholders/teams to understand requirements and develop a working solution.
- Ability to work within tight deadlines and effectively prioritise and complete tasks in a high-pressure environment.
- Must be able to mentor junior staff.
Advantageous to have experience on below:
- Hands-on with Databricks for unified data analytics, including Databricks Notebooks, Delta Lake, and Catalogues.
- Proficiency in using the ELK (Elasticsearch, Logstash, Kibana) stack for real-time search, log analysis, and visualisation.
- Strong background in analytics, including the ability to derive actionable insights from large datasets and support data-driven decision-making.
- Experience with data visualisation tools like Tableau, Power BI, or Grafana.
- Familiarity with Docker for containerization and Kubernetes for orchestration.
Skills
Apache Spark, HDFS, Hadoop, MapReduce, Python, Scala, Spark, YARN