Data Engineer

• Utveckla och förvalta datalösningar i lakehouse-arkitektur
• Bygga och vidareutveckla data pipelines
• Säkerställa hög datakvalitet och affärsnytta

Data Engineer, BI-utvecklare

• Design, develop, and maintain data pipelines on the Databricks platform
• Build and optimize scalable data integration and transformation solutions
• Work directly with Databricks notebooks, jobs, clusters, and workflows
• Develop reliable and performant solutions for processing large volumes of data
• Implement modern data modeling approaches using dbt
• Ensure high standards for data quality, traceability, scalability, and performance
• Contribute to the architecture and evolution of the organization's Azure-based data platform
• Establish and improve engineering best practices

Senior Data Engineer – Databricks Platform, Azure

• Design, build, and deploy large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies.
• Lead system-wide architectural decisions, focusing on data flow, performance, and resilience.
• Actively contribute to the codebase with high quality code.
• Lead major technical initiatives, reduce technical debt and ensure the platform meets the reliability and scalability SLAs.
• Collaborate with product and engineering teams and R&D management to define the technical roadmap, review architecture and mentor junior engineers

Principal Data Engineer

• Designa, utveckla och underhålla skalbara datapipelines
• Bygga och vidareutveckla moderna dataplattformar
• Säkerställa hög datakvalitet, säkerhet och förvaltningsbarhet
• Arbeta med Python, SQL och moderna dataverktyg
• Implementera lösningar inom Databricks, Microsoft Fabric, Apache Spark och liknande plattformar
• Omvandla verksamhetsbehov till robusta tekniska lösningar
• Delta i tekniska diskussioner kring arkitektur, kvalitet och långsiktighet
• Utforska och använda AI-verktyg för att effektivisera utvecklingsarbetet

• Utveckla och vidareutveckla datapipelines och ETL-flöden
• Arbeta med datamodellering och datahantering i Azure Cloud
• Delta i uppbyggnaden av en ny analysplattform baserad på medallion architecture
• Arbeta med Databricks, Delta Lake och Azure Data Factory
• Bidra i migrering från on-prem till molnbaserad Azure-miljö
• Samarbeta nära verksamheten och olika intressenter
• Dokumentera lösningar och bidra till kunskapsöverföring
• Delta i agila utvecklingsprocesser och arbete i Azure DevOps

Junior Data Engineer

• Arbeta med stora datamängder, både strukturerad och ostrukturerad data
• Säkerställa att data kan användas på ett effektivt, säkert och spårbart sätt i moderna data- och AI-lösningar
• Bidra till att bygga, utveckla och kvalitetssäkra dataflöden, datamodeller och datagrund för analys, beslutsstöd och AI-tillämpningar
• Säkerställa AI-läsbara dataformat, tydlig metadata, spårbarhet och hög datakvalitet

Data Engineer, 5+ års Erfarenhet

• Design and develop analytical solutions on SAP data, primarily in SAP BW and BW/4HANA environments
• Work with high-volume data flows and help shape scalable, robust data platforms for analytics
• Deploy analytical features across SAP BW and other SAP OLTP systems based on stakeholder needs
• Model and integrate data using HANA modelling, CDS Views, and provisioning to and from SAP BW
• Contribute to frontend analytics solutions using SAP Analytics Cloud and Power BI
• Support work related to Datasphere, data integration, and data volume management
• Collaborate closely with product leadership and engineers to align on priorities, delivery, and key results
• Lead programming sessions, present solution approaches, and help the team solve complex technical challenges
• Facilitate Scrum events and help the team strengthen Agile development practices in day-to-day work
• Coach colleagues and stakeholders in Scrum theory, practices, rules, and values

Senior Data Engineer – SAP Analytics

• Design, build, and maintain scalable batch and streaming pipelines using bronze/silver/gold architectures
• Develop reusable transformation frameworks and production-grade Spark workloads
• Implement and optimize Delta Lake solutions, including: ACID transactions, Partitioning strategies, Schema evolution, OPTIMIZE/ZORDER, Incremental and CDC processing patterns
• Configure and manage Unity Catalog permissions, governance, lineage, and auditability
• Perform Spark performance tuning and observability monitoring
• Integrate Databricks with Azure services including ADLS, ADF/Synapse, Key Vault, and Microsoft Entra ID
• Implement CI/CD pipelines and deployment automation using Azure DevOps or GitHub Actions
• Collaborate with architects, analysts, data scientists, and engineers to align technical implementation with business needs
• Continuously improve platform performance, reliability, cost efficiency, and standardization

Azure Databricks Data Engineer

• Designa, utveckla och underhålla skalbara datapipelines och ETL-processer med Azure och Databricks
• Importera, transformera och modellera data från olika källor för tillförlitlig analys och rapportering
• Utveckla semantiska modeller och skapa Power BI-rapporter för datadrivet beslutsfattande
• Utföra datakvalitetskontroller och säkerställa dataintegritet och säkerhet
• Dokumentera och kommunicera dataprocesser och resultat
• Stödja initiativ kring datamedvetenhet och utbildning inom organisationen
• Samarbeta med affärsintressenter för att förstå krav och leverera effektiva datalösningar

• Design, develop, and maintain scalable data pipelines and ETL processes using Azure and Databricks
• Ingest, transform, and model data from diverse sources to enable reliable analytics and reporting
• Develop semantic models and create Power BI reports to support data-driven decision making
• Perform data quality checks, ensuring data integrity and security
• Document and communicate data engineering processes and outcomes
• Support data awareness and training initiatives within the organization
• Collaborate with business stakeholders to understand requirements and deliver effective data solutions

Data Engineer – Azure, Databricks

• Design, develop, and maintain crucial data infrastructure supporting credit risk models.
• Ensure data availability, accuracy, and reliability by collaborating with Quantitative modelers, experts, and stakeholders.
• Develop scalable data pipelines and integrate diverse sources.
• Ensure high data quality and governance with Data Stewards.
• Optimize and automate processes for efficient reporting and robust risk assessments, making a significant impact on analytical capabilities.

Data Engineer – Credit Risk

• Analyze user behavior, product performance, and key business metrics to identify trends and opportunities.
• Create and maintain interactive dashboards and reports using tools like Tableau, Looker, Power BI, or Google Data Studio.
• Collect, clean, and structure large datasets to ensure accuracy and usability.
• Define and track KPIs for marketing, product, and business performance.
• Work with SQL, Python, or R to extract, analyze, and manipulate data.
• Collaborate with product managers, engineers, and marketing teams to provide data-driven insights.
• Conduct A/B testing and experiment analysis to improve product features and user engagement.
• Identify bottlenecks and opportunities in user journeys and customer funnels.
• Present findings in a clear and compelling way to stakeholders and leadership teams.
• Stay up to date with industry trends, analytics best practices, and emerging data tools.

• You will build and migrate modern data solutions in a cloud-based environment.
• You will develop and maintain data pipelines and data transformations using GCP services and tools such as BigQuery, Cloud Run, Cloud Functions, Pub/Sub, Dataflow, and Cloud Composer.
• You will work hands-on with SQL, Python, and DBT to structure, transform, and deliver data for downstream use.
• You will use Terraform to manage infrastructure as code and help create stable, repeatable deployments.
• You will contribute to version control workflows in GitHub and support efficient collaboration in the development process.
• You will work with DevOps practices and CI/CD pipelines to improve quality, automation, and delivery flow.
• You will collaborate with stakeholders and team members in an Agile setup and help move the migration forward in a practical and structured way.

• Take a key role in a global ERP and analytics transformation
• Build, improve, and maintain data solutions in Databricks
• Migrate data pipelines from the service layer into silver and gold layers in a medallion architecture
• Set up, configure, and manage jobs to support stable and efficient data processing
• Troubleshoot and resolve issues in existing pipelines and data flows
• Contribute to improving the overall structure and quality of the analytics platform
• Collaborate with teams working with ERP development and global rollout to support data and reporting needs

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Data Engineer, BI-utvecklare

Senior Data Engineer – Databricks Platform, Azure

Principal Data Engineer

Data Engineer

Junior Data Engineer

Data Engineer, 5+ års Erfarenhet

Senior Data Engineer – SAP Analytics

Azure Databricks Data Engineer

Data Engineer

Data Engineer – Azure, Databricks

Data Engineer – Credit Risk

Data Engineer

Data Engineer

Senior Data Engineer – Databricks