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Senior Data Platform Engineer

Summary

Design and maintain a hybrid-cloud data platform (AWS + GCP/BigQuery) for a European fintech, building data lakes, orchestrating pipelines, and optimizing costs to power analytics and AI transformation.

N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact.

We're looking for a Senior Data Platform Engineer to architect and operate data infrastructure across the client's hybrid cloud (AWS + GCP).

Our client is a fast-growing European fintech company in the business spend management space — corporate cards and related financial products — serving SME and mid-sized business customers across the EU and UK, in a regulated environment with GDPR compliance obligations. Engineering is organized into cross-functional squads, with platform/enabling teams providing shared tooling horizontally.

The client is currently in an AI transformation phase, transitioning to Agentic AI Development, and is seeking a Senior Data Platform Engineer to support this transformation. They run a hybrid cloud setup: AWS-first overall, with GCP (BigQuery as primary data warehouse) for data platform and analytics workloads. The Data Platform Engineer will set up and maintain the data infrastructure (data lakes, pipelines, IAM, observability, cost optimisation) that Data Engineers then use to operate on data. Work is expected to be a mix of existing codebase and new functionality.

Responsibilities:

  • Architect and operate data infrastructure across hybrid cloud (AWS + GCP).
  • Design data lakes; orchestrate pipelines (e.g. Airflow).
  • Manage IAM/access management and cost optimisation.
  • Maintain observability across the data platform.
  • Work with both BigQuery and AWS data lake patterns (Athena, S3, Glue).
  • Multiply the output and quality of the squad you join, and share patterns/practice beyond your immediate team so adoption compounds across the organisation.
  • Embed directly into a client squad as a hands-on Individual Contributor (not a coaching/managerial role).

Requirements:

  • Hybrid cloud: AWS and GCP.
  • Data lake design.
  • Orchestration, e.g. Airflow.
  • IAM/access management.
  • Cost optimisation.
  • Observability.
  • BigQuery and AWS data lake patterns (Athena, S3, Glue).
  • Python.

Nice to have:

  • Terraform.
  • Familiarity with fintech-specific domains such as fraud/AML, transaction monitoring, and regulatory compliance.

We offer*:

  • Flexible working format - remote, office-based or flexible
  • A competitive salary and good compensation package
  • Personalized career growth
  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
  • Active tech communities with regular knowledge sharing
  • Education reimbursement
  • Memorable anniversary presents
  • Corporate events and team buildings
  • Other location-specific benefits

*not applicable for freelancers

What this application asks

greenhouse

First Name, Last Name, Email, Phone, Resume/CV

  • LinkedIn Profile optional
  • Portfolio link written answer · optional
  • Country choose one
  • City choose one · optional
  • Could you please specify how many years of commercial experience you have with: Python: Apache Airflow: AWS: GCP: written answer · optional
  • Which AWS services have you worked with (Athena, S3, Glue)? Also, how much experience do you have with BigQuery? written answer · optional
  • Do you have hands-on experience designing Data Lakes and architecting data infrastructure? written answer · optional
  • Have you built autonomous or semi-autonomous AI agents specifically for code generation, refactoring, or code analysis? written answer · optional