Version 1

Technology

SeniorDataEngineer

₹25–45L ~AI est. Mumbai, Maharashtra, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Senior Data Engineer at Version 1. Skills: Data Engineering, Cloud Platforms, Data Pipelines, AWS. Design data pipelines. Build data pipelines”

Industry & Context.

Technology
Problems you'll solve

Troubleshooting issues

What They're Looking For.

Must Have

5+ years’ experience in data engineering, Databricks data engineering skills, Python programming skills, Java programming skills, Spark programming skills, Advanced SQL programming skills, Experience building data pipelines, Experience running data pipelines, Solid understanding of distributed systems, Solid understanding of scalable data architectures, AWS data services experience, Cloud-native platforms experience, Databricks experience, Data modeling understanding, Data quality approaches understanding, Batch data pipelines experience, Streaming data pipelines experience, CI/CD familiarity, Monitoring familiarity, Operational support familiarity, Troubleshoot production systems

Nice to Have

Experience enabling ML workloads, Experience enabling AI workloads, Experience enabling GenAI workloads, Exposure to modern BI tooling, Exposure to analytics tooling, Experience in regulated environments, Experience in security-conscious environments, Consulting delivery experience, Client-facing delivery experience

What You'll Do.

Design data pipelines

Operate data pipelines

Engineer cloud-native data platforms

Work with distributed processing frameworks

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

Contribute to technical design

Improve system performance

Improve system scalability

Improve system reliability

Support production systems

Implement improvement

How You'll Work.

Team & Collaboration

Analysts; Data scientists; AI engineers; Platform teams

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 co

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