Are you an experienced Data Engineer with a passion for scalable data pipelines and data-driven architectures?
We are looking for a technological leader to shape our data strategy and lead a team of experts.
...
General Information:
- Start date: asap
- latest Start Date: 1.9.25
- Planned duration: 31.8.26
- Extension (in case of limitation): possible
- Workload: 100%
- Working hours: Standard
Tasks & Responsibilities:
- Lead Data Pipelines & Storage: Design and build scalable data pipelines for real-time and batch processing. Drive architectural decisions and long-term planning for scalable, FAIR data products.
- High-Quality Data Products: Create high-quality data products adhering to FAIR principles. Address complex challenges, ensure compliance, and make strategic decisions to shape data roadmaps.
- Collaboration & Integration: Model data landscapes, acquire data extracts, and define secure exchange methods in collaboration with experts and cross-functional teams.
- Data Ingestion & Processing: Ingest and process data from diverse sources into Big Data platforms (e.g., Snowflake). Develop ERDs and reusable pipelines for advanced analytics.
- Technical Guidance & Governance: Contribute to our Data Mesh Engineering Collective to establish data governance standards, ensure regulatory compliance and data security. Mentor others and promote best practices.
- Information Security & Infrastructure Collaboration: Ensure adherence to information security standards. Collaborate with infrastructure teams for tailored tech stacks. Make independent decisions on data strategies.
- Innovation & Knowledge Sharing: Shape the data engineering roadmap and set standards for data quality and governance. Proactively share best practices.
- Technical Proficiency: Maintain proficiency in data engineering tech stacks, data quality, and observability tools (e.g., Ataccama, Monte Carlo).
- Adherence to Standards: Ensure compliance with relevant guidelines and data governance standards. Develop long-term enterprise tools.
Must Haves:
- Master’s degree in Computer Science, Data Engineering, or a related field.
- Over 5 years in data engineering with a track record in architecting and scaling large data systems.
- 5+ years of experience in leading and mentoring data engineers.
- Proven experience in building and managing data pipelines and products.
- Skilled in handling structured, semi-structured, and unstructured data.
- Proficiency in Python, Java, SQL, or Scala, and experience with big data technologies (e.g., Hadoop, Spark).
- Expertise in multiple cloud platforms (AWS, Azure, GCP) and data warehousing technologies (preferably Snowflake).
- Deep understanding of Information Security to ensure compliant handling and management of process data.
- Familiarity with data modeling and ETL tools.
- Knowledge of version control systems like Git and CI/CD pipelines.
- Proficiency in implementing robust testing practices and monitoring pipelines for performance, reliability, and data quality.
- Client-facing project experience.
- Proven ability to communicate complex solutions to varied technical audiences.
- Strong organizational and interpersonal skills for delivering results and optimizing resources.
- Ability to work independently and collaboratively within a team environment.
- Strong ability to influence and collaborate with stakeholders, trust building and reliable delivery of solutions
We thank you for your application!
Are you an experienced Data Engineer with a passion for scalable data pipelines and data-driven architectures?
We are looking for a technological leader to shape our data strategy and lead a team of experts.
General Information:
- Start date: asap
- latest Start Date: 1.9.25
- Planned duration: 31.8.26
- Extension (in case of limitation): possible
- Workload: 100%
- Working hours: Standard
... Tasks & Responsibilities:
- Lead Data Pipelines & Storage: Design and build scalable data pipelines for real-time and batch processing. Drive architectural decisions and long-term planning for scalable, FAIR data products.
- High-Quality Data Products: Create high-quality data products adhering to FAIR principles. Address complex challenges, ensure compliance, and make strategic decisions to shape data roadmaps.
- Collaboration & Integration: Model data landscapes, acquire data extracts, and define secure exchange methods in collaboration with experts and cross-functional teams.
- Data Ingestion & Processing: Ingest and process data from diverse sources into Big Data platforms (e.g., Snowflake). Develop ERDs and reusable pipelines for advanced analytics.
- Technical Guidance & Governance: Contribute to our Data Mesh Engineering Collective to establish data governance standards, ensure regulatory compliance and data security. Mentor others and promote best practices.
- Information Security & Infrastructure Collaboration: Ensure adherence to information security standards. Collaborate with infrastructure teams for tailored tech stacks. Make independent decisions on data strategies.
- Innovation & Knowledge Sharing: Shape the data engineering roadmap and set standards for data quality and governance. Proactively share best practices.
- Technical Proficiency: Maintain proficiency in data engineering tech stacks, data quality, and observability tools (e.g., Ataccama, Monte Carlo).
- Adherence to Standards: Ensure compliance with relevant guidelines and data governance standards. Develop long-term enterprise tools.
Must Haves:
- Master’s degree in Computer Science, Data Engineering, or a related field.
- Over 5 years in data engineering with a track record in architecting and scaling large data systems.
- 5+ years of experience in leading and mentoring data engineers.
- Proven experience in building and managing data pipelines and products.
- Skilled in handling structured, semi-structured, and unstructured data.
- Proficiency in Python, Java, SQL, or Scala, and experience with big data technologies (e.g., Hadoop, Spark).
- Expertise in multiple cloud platforms (AWS, Azure, GCP) and data warehousing technologies (preferably Snowflake).
- Deep understanding of Information Security to ensure compliant handling and management of process data.
- Familiarity with data modeling and ETL tools.
- Knowledge of version control systems like Git and CI/CD pipelines.
- Proficiency in implementing robust testing practices and monitoring pipelines for performance, reliability, and data quality.
- Client-facing project experience.
- Proven ability to communicate complex solutions to varied technical audiences.
- Strong organizational and interpersonal skills for delivering results and optimizing resources.
- Ability to work independently and collaboratively within a team environment.
- Strong ability to influence and collaborate with stakeholders, trust building and reliable delivery of solutions
We thank you for your application!
