Data Engineer

• Leading and developing the Data Engineering team across Poland and Denmark (8 colleagues)
• Owning the engineering backbone of the data platform (ingestion, transformation, orchestration, observability)
• Ensuring stable, predictable, and cost-efficient operation of data pipelines
• Driving engineering standards and best practices (CI/CD, testing, documentation)
• Implementing and enforcing governance on data quality, security, and cost
• Supporting a data mesh model by enabling domains to build and operate their own data products
• Working closely with Data Science and AI initiatives to ensure the platform supports current and future use cases
• Translating strategy into concrete engineering roadmaps and executable delivery plans
• Ensuring compliance with VELUX policies on data, privacy, security, and responsible AI

Head of Data Engineering

• Design and implement scalable data platforms and pipelines across cloud environments (Azure/Fabric, AWS, GCP, Databricks, Snowflake)
• Developing reliable batch, streaming, and near-real-time pipelines
• Ensure adherence to best practices in data governance, lineage, quality, and access control (RBAC/ABAC)
• Establish strong data observability, including monitoring of data freshness and pipeline reliability
• Work closely with data scientists, ML engineers, analysts, and business stakeholders to translate requirements into robust data solutions

Senior Data Engineer

• Enable Parexel’s data movement within the Enterprise Data Lake
• Deliver standardized operational data products across clinical, safety, and corporate domains
• Contribute to data lake strategy, engineering, and operations
• Ensure trusted, high-quality, and well-governed data
• Serve as a subject matter expert in data delivery
• Lead engineering activities across data ingestion, transformation, storage, and optimization within the Enterprise Data Lake
• Oversee the performance, quality, reliability, security, and lifecycle management of data in the lake environment
• Ensure scalable engineering pipelines across data domains
• Build, mentor, and lead global data engineering teams
• Promote a culture of innovation, operational rigor, and customer-focused delivery

Associate Director, Data Engineering

• Working with all DSV business divisions as well as group functions to simplify information gathering and turning data into insight
• Design and implement solutions that will support the development of our Operational Data Warehouse (ODW) in alignment with IT and BI architecture principles, guidelines, and standards
• Develop and maintain scalable data pipelines for ingesting, processing and transforming large volumes of data from various sources
• Analyse requirements together with our different department teams and create effort estimations and implementation planning
• Document and provide technical specifications for the implementations
• Refine and promote our agile delivery framework to help ensure high quality and flexible deliverables on the data & BI platform
• Support different department teams in a collaborative work environment
• Actively transfer knowledge to other team members as well as the Operations & Support team

• Building data solutions that enable clients and business partners to make efficient decisions.
• Designing robust solutions on state-of-the-art compute engines like Databricks and modern data warehousing solutions like MS Fabric or Snowflake.
• Solving complex business problems on a large scale.
• Participating in cross-functional initiatives and collaborating across various domains.
• Interacting with engineers, product/project managers, and partners from all over the world.

• tworzenie i utrzymywanie przepływów danych (ETL/ELT)
• pisanie oraz optymalizacja zapytań SQL do czyszczenia, transformacji i walidacji danych
• monitorowanie działania przepływów danych oraz rozwiązywanie problemów
• tworzenie i utrzymywanie przepływów danych w Pythonie
• analiza danych i wspieranie innych zespołów w pracy z danymi

Junior Data Engineer

• Monitor and support the Production Data Warehouse environment
• Troubleshoot and resolve issues related to ETL jobs, data loads, and performance bottlenecks
• Coordinate with development, infrastructure, and business teams to ensure smooth operations and incident resolution
• Perform root cause analysis for incidents and recurring issues and contribute to the continuous improvement of support and maintenance processes.

Data Warehouse Support Specialist

• Responsible for building data platforms that enable our clients and business partners to make efficient decisions with ease.
• Design robust solutions on state-of-the-art data engines such as Snowflake.
• Participate in international projects mostly based on and implemented using major three cloud providers (Azure, GCP, AWS).

Senior Data Engineer, Snowflake

• Architect, design, and lead the technical execution of modernizing enterprise Master Data Management systems by integrating AI/ML capabilities for data matching, entity resolution, and data enrichment
• Act as the primary technical architect for the foundational Healthcare Professional (HCP), Healthcare Organisation (HCO), and Business Partner/Vendor master data initiatives, ensuring high-fidelity modeling and scalability for subsequent domains
• Define the blueprints and mapping rules required to connect transactional master data with unified semantic layers, ontologies, and enterprise knowledge graphs
• Ensure that master data models are fully machine-readable and explicitly structured to serve as the "ground truth" for Large Language Models (LLMs), effectively mitigating hallucinations through semantic mapping
• Act as the crucial technical bridge between raw infrastructure engineers, data platform managers, and business-focused clinical stakeholders to align technological implementation with industry context
• Evaluate and integrate emerging semantic technologies and vendor systems to continuously reduce technical debt within the data management layer while ensuring compliance by design

Data Architect – Data Platforms

• Lead the design and implementation of end-to-end finance process workflows and data architectures across all core domains (P2P, R2R, O2C, P2D, Tax, Treasury), ensuring alignment with business needs, scalability, and compliance
• Define finance requirements and drive the selection and implementation of ERP and finance platforms (e.g., SAP S/4HANA), working closely with IT while retaining ownership on the finance side
• Establish and enforce data governance standards, ensuring accuracy, consistency, and security of financial data, and aligning data models and flows with business and regulatory requirements
• Lead a small core team and orchestrate delivery across a broader network of Finance, IT, and business stakeholders to ensure successful execution of transformation initiatives
• Define KPIs and performance metrics for finance processes and data architecture, monitor effectiveness, and drive continuous improvement and efficiency gains
• Partner with Finance GPOs, Function Leads, and business stakeholders to translate requirements into practical solutions, while identifying opportunities to leverage new technologies (including AI) to enhance finance operations

Finance Process and Data Architecture Lead

• Take ownership of the company’s data stack, including BigQuery and Looker Studio environments
• Build and maintain real-time reporting pipelines for marketing spend and campaign performance
• Implement and manage tracking pixels, server-to-server (S2S) integrations, and event tracking systems
• Design and improve attribution models to support data-driven marketing decisions
• Serve as the technical point of contact for the User Acquisition team regarding tracking, APIs, URLs, naming conventions, and troubleshooting
• Develop automation solutions to improve reporting workflows and operational efficiency
• Build inventory forecasting pipelines across Shopify, Amazon, TikTok Shop, and other ecommerce channels
• Collaborate cross-functionally with marketing, operations, and analytics stakeholders to improve reporting accuracy and business visibility

• Build and maintain scalable data pipelines using Spark, Databricks, and cloud platforms
• Design data models for analytics, ML, and AI applications
• Drive adoption of AI tools and agentic workflows within the data engineering team
• Identify and implement ways to improve engineering efficiency using AI
• Prototype and scale AI-assisted development practices
• Act as a go-to expert for AI experimentation and knowledge sharing
• Help establish best practices and contribute to an AI-focused community or guild
• Build pipelines supporting ML models, LLM applications, and AI workflows
• Ensure data quality, observability, and reliability
• Collaborate with Product, Data Science, ML/AI, and DevOps teams

AI Data Engineer

• odpowiedzialność za całość rozwiązań współtworzonych wraz z zespołem
• tworzenie lub modyfikowanie rozwiązań do przetwarzania danych w chmurze
• tworzenie i modyfikowanie dokumentacji
• analizowanie i optymalizowanie rozwiązań w zakresie działającego lub projektowanego systemu
• analizowanie wymagań klienta pod kątem dostarczenia optymalnego rozwiązania jego potrzeby biznesowej
• analizowanie potencjalnych zagrożeń
• dostosowywanie rozwiązań względem wymagań biznesowych
• testowanie rozwiązań.

Senior Cloud Data Engineer, AWS, GCP, Databricks

• Implementation and maintenance of the CDP environment (collector, enrich, loaders)
• Integration of event data from various sources
• Configuration and development of the CDP (schema repository)
• Building and maintaining data pipelines in the cloud (AWS)
• Creating and developing analytical models and integration with the data catalog
• Participating in the development and implementation of user identification mechanisms (ID stitching, cross-device, cross-site, consent logic)
• Documentation and collaboration with Data Engineering, Data Management, Data Governance, IT, Privacy, and Analytics teams

CDP Data Engineer

• Design semantic, logical, and conceptual data models based on business domains and organizational processes.
• Define and standardize the corporate data model as part of the Data Governance initiative.
• Create and maintain reference architecture (logical and technical reference architectures) and design patterns for data domains.
• Co-create the strategy and roadmap for data architecture development that supports the vision of the Data Governance program and organizational goals.
• Collaborate with Data Governance, Data Management, Analytics, AI, and Data Engineering teams to integrate models with the data catalog and metadata management tools.
• Support technical teams in implementing models in data layers.
• Participate in designing data integration, flow, and quality processes (data lineage, data contracts, data quality).
• Identify and certify authoritative data sources within organizational domains.
• Monitor the compliance of data solutions with Data Governance policies and standards as well as architectural recommendations.
• Support the resolution of data conflicts and issues.
• Create architectural documentation, metamodels, and inter-domain relationship diagrams.
• Consult on and develop good practices in the area of modeling, metadata, and information architecture.
• Collaborate on defining the vision, priorities, and directions for the development of data architecture in the organization.

Corporate Data Architect

• Design and implement batch and real time ingestion pipelines from internal and external sources
• Implement automated data quality checks, observability, and SLA monitoring
• Support master data management, metadata, lineage, and access controls
• Optimise datasets and pipelines for analytics, ML training, and API consumption
• Work closely with Data Scientists and ML Engineers to support feature and model needs
• Contribute to long term platform roadmap and AI readiness

• Design, build, and optimize high-volume, high-performance ELT pipelines for centralized data warehousing
• Collaborate with Product Managers, ML Engineers, Data Scientists, and DevOps to define and enforce a reliable, scalable, and secure data platform architecture
• Ensure adherence to data warehousing standards, data quality best practices, and metadata management processes
• Take responsibility for assigned data warehouse components, contributing to enhancements in performance and reliability
• Conduct architecture reviews and participate in system design discussions to provide technical input
• Support and collaborate with peers, sharing knowledge and promoting a culture of quality and continuous learning

Data Engineer – Interior Design

• Design, build, and operate scalable, reliable data pipelines and data infrastructure
• Ensure high-quality data is accessible, trusted, and ready for analytics and data science
• Build and maintain data pipelines for ingestion, transformation, and export across multiple sources and destinations
• Develop and evolve scalable data architecture to meet business and performance requirements
• Partner with analysts and data scientists to deliver curated, analysis-ready datasets and enable self-service analytics
• Implement best practices for data quality, testing, monitoring, lineage, and reliability
• Optimize workflows for performance, cost, and scalability (e.g., tuning Spark jobs, query optimization, partitioning strategies)
• Ensure secure data handling and compliance with relevant data protection standards and internal policies
• Contribute to documentation, standards, and continuous improvement of data platform and engineering processes
• Ensure secure, compliant handling of data and models, including access controls, auditability, and governance practices
• Build and maintain MLOps automation: CI/CD for ML, environment management, artifact handling, versioning of data/models/code

Data Engineer – Contractor

• Lead the design and implementation of end-to-end finance process workflows and data architectures across all core domains (P2P, R2R, O2C, P2D, Tax, Treasury), ensuring alignment with business needs, scalability, and compliance
• Define finance requirements and drive the selection and implementation of ERP and finance platforms (e.g., SAP S/4HANA), working closely with IT while retaining ownership on the finance side
• Establish and enforce data governance standards, ensuring accuracy, consistency, and security of financial data, and aligning data models and flows with business and regulatory requirements
• Lead a small core team and orchestrate delivery across a broader network of Finance, IT, and business stakeholders to ensure successful execution of transformation initiatives
• Define KPIs and performance metrics for finance processes and data architecture, monitor effectiveness, and drive continuous improvement and efficiency gains
• Partner with Finance GPOs, Function Leads, and business stakeholders to translate requirements into practical solutions, while identifying opportunities to leverage new technologies (including AI) to enhance finance operations.

See all jobs on JobTailor

Head of Data Engineering

Senior Data Engineer

Associate Director, Data Engineering

Data Engineer

Senior Data Engineer

Data Engineer

Junior Data Engineer

Data Warehouse Support Specialist

Senior Data Engineer, Snowflake

Data Architect – Data Platforms

Finance Process and Data Architecture Lead

Data Engineer

AI Data Engineer

Senior Cloud Data Engineer, AWS, GCP, Databricks

CDP Data Engineer

Corporate Data Architect

Data Engineer

Data Engineer – Interior Design

Data Engineer – Contractor

Finance Process & Data Architecture Lead