Staff Software Engineer

Job Summary

Overview About Business Unit: The Automotive Practice at Epsilon is a rapidly growing team, driving growth for major players in the automotive industry - from Original Equipment Manufacturers (OEMs) to dealerships across North America. Part of a 1,600-member multinational team, the practice provides the automotive world s largest service reminder platform, alongside agency services and digital media solutions. A leader in the automotive space, the team supports over 50% of auto dealerships in North America and maintains relationships with over 280 million customers. Home to innovation and ground breaking technology, our Auto team leads the game in developing outstanding software and solutions for hyper-personalized digital marketing. Summary: We are looking for a Staff with 10+ years of experience to lead Oracle, ETL/Data Engineering, Databricks and AI driven solution architecture. The role requires deep experience in enterprise data platforms, Oracle database engineering, data warehousing, cloud data modernization and production-grade AI/GenAI capabilities. Define data architecture strategy, technical roadmaps and modernization patterns for enterprise platforms. Design scalable Oracle, ETL/ELT, Databricks and cloud data solutions for analytics, reporting and AI workloads. Partner with Product, Engineering, QA, Data Science and Business teams to convert requirements into secure, reliable and extensible solutions. Establish architecture standards, governance, reusable design patterns and engineering guidelines. Click here to view how Epsilon transforms marketing with 1 View, 1 Vision and 1 Voice.

Responsibilities

• Analyze existing data ecosystems and recommend improvements for performance, scalability, reliability and maintainability.
• Design enterprise data models, data warehouses, ETL/ELT frameworks, integration patterns and data quality controls.
• Architect batch and streaming pipelines using Oracle, Databricks, Apache Spark, Delta Lake and AWS services.
• Lead modernization from legacy platforms to cloud-native, lakehouse and AI-enabled architectures.
• Drive implementation of GenAI capabilities including LLM integration, RAG, embeddings, vector search and intelligent automation.
• Create architecture documents, solution blueprints, data flow diagrams, implementation plans and technical specifications.
• Guide design reviews, code reviews, production readiness reviews, RCA and complex issue resolution.
• Mentor engineers and technical leads while working with globally distributed teams and senior partners.

Qualifications

• The candidate should bring a balanced mix of hands-on technical depth, architecture leadership, stakeholder communication and ownership mentality.
• Core Experience: 10+ years in data architecture, Oracle database engineering, data warehousing, ETL/ELT, data integration or enterprise application development.
• Oracle Data Platforms: Expertise in Oracle Database, SQL, PL/SQL, Unix/Linux, performance tuning, data modeling, schema design, data warehousing and large relational databases.
• Data Engineering: Strong experience designing reusable ETL/ELT frameworks, batch/streaming pipelines, data quality checks, metadata practices and scalable data processing solutions.
• Databricks Cloud: Hands-on exposure to Databricks, Apache Spark, Delta Lake, lakehouse architecture and AWS-based data platform modernization.
• AI / GenAI: Experience or strong working knowledge of LLMs, RAG, embeddings, vector databases, prompt engineering, AI monitoring, evaluation and production AI integration patterns.
• Engineering Practices: Working knowledge of Python, shell scripting, CI/CD, DevOps, APIs, test planning, documentation, observability, security and SDLC practices.
• Leadership: Ability to define architecture roadmaps, influence technical direction, mentor teams, manage trade-offs and communicate with technical and non-technical partners.
• Domain Delivery: Automotive marketing, CRM, customer data platforms, AdTech or MarTech experience is preferred. Must be comfortable with distributed teams, tight timelines and production critical platforms.
• Behavioral Attributes: Strong ownership, analytical thinking, problem-solving mindset, learning agility, collaboration, clear communication and a can-do attitude.
• Education: Bachelors or Masters degree in Computer Science, Information Technology, Engineering or a related field, or equivalent professional experience.

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