Version 1
Technology
SeniorDataEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Senior Data Engineer at Version 1. Skills: Data Engineering, Cloud-native data solutions, Data pipelines, AWS. Design data pipelines. Build data pipelines”
Industry & Context.
Solving complex data challenges; Troubleshooting issues
What They're Looking For.
Must Have
5+ years experience, Databricks data engineering skills, Python programming skills, Java programming skills, Spark programming skills, Advanced SQL programming skills, FS experience, Build and run data pipelines, Solid understanding of distributed systems, Solid understanding of scalable data architectures, AWS data services experience, Cloud-native platforms experience, Databricks or similar experience, Solid understanding of data modeling, Solid understanding of data quality approaches, Build and operate batch data pipelines, Build and operate streaming data pipelines, CI/CD familiarity, Monitoring familiarity, Operational support familiarity, Contribute to technical design, Improve system performance, Improve system scalability, Improve system reliability, Support production systems, Troubleshoot issues, Implement improvements
Nice to Have
ML workload enablement experience, AI workload enablement experience, GenAI workload enablement experience, Modern BI tooling exposure, Analytics tooling exposure, Regulated environments experience, Security-conscious environments experience, Consulting experience, Client-facing delivery experience
What You'll Do.
Design data pipelines
Operate data pipelines
Engineer cloud-native data platforms
Work with technologies
Ensure solutions are production-ready
Ensure solutions are secure
Ensure solutions are tested
Ensure solutions are observable
Ensure solutions are cost-efficient
Optimize data performance
Optimize data reliability
Optimize data quality
Collaborate with analysts
Collaborate with data scientists
Collaborate with AI engineers
Collaborate with platform teams
Mentor junior engineers
Contribute to shared standards
Contribute to accelerators
Troubleshoot production issues
Implement production improvements
How You'll Work.
Team & Collaboration
Analysts; Data scientists; AI engineers; Platform teams; Junior engineers
Full Job Description
Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services. We’re an award-winning employer reflecting how our employees are at the very heart of what we do: * UK & Ireland's premier AWS, Microsoft & Oracle partner * 3300+ strong, €350/£300m revenue business * 10+ years as a Great Place to Work in Ireland & UK * Best Workplace for Women in the UK & Ireland by GPTW * Best Workplace for Wellbeing in the UK by GPTW We’re a core values driven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you!. The Role We are looking for a Senior Data Engineer to join Version 1’s Data & AI Practice, working on modern data platforms for enterprise and regulated clients. You will be a hands‑on engineer with strong production experience, contributing to the design, build, and operation of scalable, cloud‑native data solutions that enable analytics and AI at scale. This is a delivery‑focused role for an experienced engineer who enjoys solving complex data challenges, takes ownership of outcomes, and applies strong engineering discipline in real‑world environments. What You’ll Be Doing * Designing, building, and operating reliable data pipelines using modern ETL/ELT approaches * Engineering cloud‑native data platforms, primarily on AWS (with Azure exposure where required) * Working with technologies such as Databricks, PostgreSQL, Aurora, and distributed processing frameworks * Ensuring solutions are production‑ready: secure, tested, observable, and cost‑effi
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