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Salary
$65k – $164k per year (Estimated)
Location
In office (Gothenburg)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match

We are looking for aSenior Databricks Data Engineer for a global company inGothenburg.

Start is in Oct 2026, 5-months limited contract to begin with, possibility of extension after that.

bout the Role

As a Senior Data Engineer, you will use Databricks as a foundation to design, build, and enable scalable reporting, analytics, and AI-driven insights. You will ensure that business-critical data is reliable, secure, governed, and accessible for approved use across the organization.

As part of the Enterprise Analytics & Insights Team, you will work closely with business stakeholders, analytics specialists, platform teams, and source-system owners to translate data needs into sustainable technical solutions. The Senior Data Engineer strengthens the organization’s data capabilities through robust architecture, integration, automation, and continuous improvement.

Key Responsibilities

- Design, develop, and maintain scalable data platforms and solutions using Databricks, including data lakes, lakehouses, data warehouses, enterprise data services, and ETL/ELT frameworks.

- Build, optimize, and support ETL/ELT pipelines and data integration workflows, integrating and harmonizing data from ERP, HR, Finance, CRM, and other enterprise systems for analytics and business consumption.

- Develop trusted and reusable data products through data modeling, metadata management, and data architecture practices while ensuring data quality, lineage, security, governance, privacy, and regulatory compliance.

- Ensure reliable and efficient data operations through monitoring, testing, automation, performance tuning, cost optimization, and recovery practices.

- Partner with business, analytics, and engineering teams to translate requirements into scalable technical solutions, while driving engineering excellence through documentation, mentoring, technical reviews, and continuous improvement.

Skill requirements

Knowledge:

  • Advanced knowledge of data engineering principles, enterprise data architecture, data integration, and cloud-based data platforms

  • Strong understanding of ETL/ELT patterns, batch and streaming concepts, orchestration, dependency management, and error handling.

  • Advanced knowledge of SQL, data modelling, dimensional modelling, data warehousing, lakehouse concepts, and analytics-ready data design.

  • Knowledge of data governance, quality, lineage, metadata, access control, privacy, retention, and secure data handling.

  • Understanding of API-based integration, file-based exchange, database connectivity, and common enterprise source-system patterns.

  • Knowledge of DevOps and DataOps practices, including version control, automated testing, CI/CD, infrastructure configuration, and release management.

  • Familiarity with analytics, business intelligence, AI, and machine learning consumption requirements.

Experience:

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field, or equivalent practical experience.

  • 5+ years of experience in data engineering, data platform development, Databricks, integration engineering, or a comparable technical role, designing and delivering scalable cloud-based data solutions and enterprise data pipelines.

  • Proven experience integrating data from multiple business domains and source systems into governed analytics platforms, supported by robust data models and structures for reporting, analytics, and advanced data use cases.

  • Experience implementing and supporting production-grade data solutions, including data quality controls, monitoring, troubleshooting, operational support, and continuous improvement.

  • Experience collaborating with business and technical stakeholders, conducting technical reviews, and supporting the development and mentoring of other engineers.

Skills:

  • Advanced SQL and strong programming or scripting capability for data transformation and automation.

  • Strong hands-on capability with cloud data services, orchestration tools, distributed processing, and data storage technologies.

  • Ability to design secure, reliable, maintainable, and cost-conscious data solutions.

  • Strong analytical troubleshooting skills across complex data flows, dependencies, and platform components.

  • Ability to translate business and analytical requirements into clear technical architecture and implementation choices.

  • Strong documentation, stakeholder communication, collaboration, and technical facilitation skills.

  • Proactive and structured way of working, with strong attention to quality, security, governance, and operational sustainability.

  • Ability to work effectively in a cross-functional, international, and evolving enterprise environment.

This is a full-time consultant position inGothenburg through Incluso. Start is in Oct 2026, 5 months limited contract to begin with. This role is 100% onsite inGothenburg.

Please submit your CV as soon as possible since we will review the applications on an on-going basis.

For more information about this role, please contact Kanika Singhal recruiter at Incluso.

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