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Senior Data Engineer - Data & AI at ARNVIND GROUP

Key Facts

Remote From: 
Category:  Data Engineer
Full time
Senior (5-10 years)
English

Other Skills

  • Communication
  • Collaboration

Roles & Responsibilities

  • Proven experience as a Data Engineer
  • Deep expertise in data modeling for analytics
  • Hands-on experience with lakehouse architectures
  • Experience developing pipelines for analytics, testing, and AI/ML use cases

Requirements:

  • Architect, build, and maintain robust data pipelines for analytics, A/B testing, and AI/ML applications
  • Design and implement analytical data models that support business metrics and data-driven decision-making
  • Develop scalable, cost-efficient, and resilient real-time data ingestion pipelines
  • Implement validation frameworks, quality checks, and monitoring for data freshness and reliability

Job description

Senior Data Engineer – Data & AI

EXO ARNVIND is partnering with a pioneering leader in Sweden’s digital healthcare and e-commerce sector to find their next Senior Data Engineer.

Our client is transforming how millions of people access essential services through cutting-edge AI, automation, and data-driven innovation.

This is a rare opportunity to join a high-impact team where your work will directly shape the future of a fast-growing, mission-driven organisation. If you’re a seasoned data engineer with a passion for building scalable, production-grade data solutions that power analytics, experimentation, and AI, this role is for you.


The Opportunity

As a Senior Data Engineer, you will play a central role in designing, developing, and evolving end-to-end data infrastructure that fuels both business intelligence and machine learning initiatives. This is a product-focused position where you’ll collaborate closely with ML engineers, software developers, product managers, and business stakeholders to ensure data is accurate, well-structured, and actionable—from ingestion to real-time dashboards and AI models in production.

You’ll own the entire data lifecycle, from collection and validation to transformation and consumption, while driving improvements to the data platform’s maturity, reliability, and scalability. This is a chance to work on high-visibility projects that impact customer experience, operational efficiency, and strategic decision-making—all within a modern, cloud-native environment.

Key Responsibilities

  • End-to-End Data Ownership: Architect, build, and maintain robust data pipelines for analytics, A/B testing, and AI/ML applications. Ensure long-term sustainability and scalability of data solutions, not just initial delivery.
  • Data Modeling & Analytics Enablement: Design and implement analytical data models that support business metrics, experimentation, and data-driven decision-making. Translate complex KPIs into reliable, trustworthy data structures.
  • Real-Time & Event-Driven Data: Partner with software engineering teams to develop scalable, cost-efficient, and resilient real-time and event-driven data ingestion pipelines.
  • Data Quality & Reliability: Implement validation frameworks, quality checks, and monitoring for data freshness, volume, schema consistency, and distribution. Define and track data SLAs/SLOs, and establish strategies for backfills, reprocessing, and recovery from data issues.
  • Platform Maturity & Engineering Excellence: Contribute to the evolution of the company’s data platform architecture. Enhance standards, tooling, and best practices across the platform, and leverage CI/CD and Infrastructure as Code (IaC) for reliable, automated deployments.

What We’re Looking For

  • Proven experience as a Data Engineer, with a track record of building end-to-end data solutions in production environments.
  • Deep expertise in data modeling for analytics and data-driven products, with a focus on scalability and usability.
  • Hands-on experience with lakehouse architectures and modern analytical data stacks.
  • Experience developing pipelines for analytics, testing, and AI/ML use cases.
  • Strong ability to interpret business metrics, derive insights, and drive actionable outcomes from data.
  • Solid understanding of data quality, validation, and observability principles.
  • Familiarity with CI/CD pipelines and Infrastructure as Code.
  • A software engineering mindset: clean, maintainable code, testing, version control, and ownership of deliverables.
  • Ability to balance rapid delivery with long-term platform maturity and reliability.
  • Excellent communication skills and a collaborative, product-oriented approach.

Nice-to-Haves

  • Experience with A/B testing platforms or experimentation frameworks.
  • Exposure to MLOps or feature store concepts.
  • Familiarity with event-driven architectures and streaming systems.
  • Experience with AWS and cloud-native data platforms.
  • Knowledge of API/Event-first design and Test-Driven Development (TDD).

Why This Role Stands Out

  • Meaningful Impact: Work on AI, ML, and automation projects that improve healthcare accessibility and customer experience for millions of users.
  • Flat & Agile Culture: Join a dynamic, cross-functional organisation with minimal bureaucracy, where your ideas are heard and your contributions matter.
  • Growth & Development: Access ongoing training, mentorship, and opportunities to attend industry conferences. Own projects from concept to deployment and see your work come to life.
  • Stability & Vision: Be part of a financially robust, future-focused company with a clear mission and ambitious growth plans.


Interested? Apply now and let us take it from there.

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