Cloud Data Engineer implementing tailored solutions for Volkswagen Group data processing. Building ETL/ELT pipelines while collaborating with technical experts.
About the role
- Data Architect responsible for designing and enforcing Medallion Architecture for AI consultancy's Lakehouse implementations with a focus on data modeling and standards.
Responsibilities
- Design and enforce Medallion Architecture for the Lakehouse.
- Drive architectural decision-making through SAF/ARB architecture forums.
- Lead design for all Data Factory squads working on data initiatives.
- Define standards for Apache Iceberg tables, including partitioning strategy, schema evolution, time travel and snapshot retention, and table optimization schedules.
- Establish data modeling standards (e.g., dimensional modeling for Gold layer, SCD2, naming conventions, metadata management).
- Define lineage standards leveraging OpenMetadata.
- Coordinate with platform teams on Iceberg-related activities.
- Collaborate with Data Quality leads to implement validation rules.
- Proactively manage escalations and communicate progress with senior stakeholders.
- Provide guidance to Glue Data Engineers.
- Establish code review processes and best practices.
- Create reusable design patterns and templates for consistency.
Requirements
- data architecture roles, ideally 10 years+ with at least 3 years in Lakehouse implementations.
- Lakehouse architecture (S3, Iceberg, Glue, Spark).
- schema evolution, partitioning strategies, and table optimization in Iceberg.
- defining metadata management, lineage, and data quality frameworks.
- Medallion architecture and data modeling principles.
- leading architectural forums and influence decision-making.
- AWS services (S3, Glue, Athena, EMR).
- Apache Iceberg, Spark.
- OpenMetadata, or similar lineage tools.
- automating work / repetitive tasks.
- communicating and stakeholder management.
- working collaboratively across multiple squads and teams.
- working in a fast-paced environment and deliver aggressive migration targets.
- working with Jira and agile way of working.
Benefits
- Competitive salary and performance bonuses
- Comprehensive health insurance
- Professional development and certification support
- Opportunity to work on cutting-edge AI projects
- Flexible working arrangements
- Career advancement opportunities in a rapidly growing AI company
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Engineer designing and optimizing data pipelines using Databricks and Google Cloud Platform. Collaborating with analysts and scientists to deliver high - quality data products.
Data Engineer responsible for building scalable data infrastructure that supports data - driven decisions. Collaborating with team to maintain systems and unlock data value for organizations.
Associate Data Engineer supporting privacy engineering controls and executing privacy impact assessments in a financial services company. Collaborating across business units to ensure alignment with privacy regulations.
Data Engineer at CVS Health optimizing data pipelines and analytical models. Driving data - driven decisions with healthcare data for improved business outcomes.
Senior Data Engineer at CVS Health developing robust data pipelines for healthcare data. Collaborating with teams to provide actionable insights and integrate them with consumer touchpoints.
Senior Data Engineer supporting AI - enabled financial compliance initiative with data pipelines and ingestion processes. Collaborating with diverse teams in a mission - critical regulated environment.
Data Architect leading the definition and construction of cloud data architecture for Kyndryl. Participating in significant technological modernization initiatives, focusing on Google Cloud Platform.
Senior Data Engineer driving data intelligence requirements and scalable data solutions for a global consulting firm. Collaborating across functions to enhance Microsoft architecture and analytics capabilities.
Experienced AI Engineer designing and building production - grade agentic AI systems using generative AI and large language models. Collaborating with data engineers, data scientists in a tech - driven company.