Jobdetails
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!
mehr anzeigen
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!
mehr anzeigen
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