Data Engineer (m/f/d)

Invenda GmbH
Ansprechpartner: Aleksandra Ivanova
München,  Deutschland
100% RemoteFreiberuflichStart 10/2026Dauer 6 Monate100% Auslastung
Medizin und PharmaApache AirflowData ArchitectureData GovernanceData TransformationData MigrationDatenendeinrichtungData VaultData WarehousingDatenbankentwicklungInfosphere DatastagePythonSQLDatenbank-EnginesAzure Data FactoryPhysical Data ModelsAzure Data AnalyticsDaten-PipelineDatabricks

Beschreibung

Role description
  1. Design and implement data pipeline architectures and integration solutions as part of defined data platform initiatives.
  2. Provide technical expertise for the design, development, and optimization of ETL/ELT processes supporting data ingestion, transformation, and consumption requirements.
  3. Design and deliver cloud-based data warehouse solutions aligned with specific project objectives and business needs.
  4. Develop conceptual, logical, and physical data models following industry best practices, including Star Schema and Data Vault methodologies.
  5. Design and implement workflow orchestration and automation solutions using Apache Airflow and dbt to enhance data platform capabilities.
  6. Deliver scalable and efficient data engineering solutions leveraging Python and SQL in accordance with agreed project requirements.
  7. Provide architectural and technical expertise for the implementation and enhancement of Azure-based cloud data platform components.
  8. Engage with business and technical stakeholders to gather requirements, validate deliverables, and provide recommendations for data solutions.
  9. Advise on the adoption and effective use of AI-powered engineering tools and data engineering best practices within the scope of the project.
Required Skills & Experience
  1. Minimum 5 years of professional experience as a Data Engineer or in a comparable role.
  2. Strong hands-on experience with Python and SQL.
  3. Proven experience with Apache Airflow and dbt.
  4. Strong background in designing and implementing ETL/ELT pipelines.
  5. Experience with modern data warehousing platforms such as Snowflake and/or Databricks.
  6. Strong understanding of data modeling techniques, including Star Schema and Data Vault.
  7. Experience working with Microsoft Azure services and cloud-based data architectures.
  8. Familiarity with AI-assisted development tools and concepts such as Claude Code, Codex, MCP, or similar technologies.
  9. Strong analytical and problem-solving skills.
  10. Excellent communication skills and ability to work in cross-functional teams.
  11. Fluent English, both written and spoken.
Nice-to-Have
  1. Experience with dltHub.
  2. Experience working in Agile environments.
  3. Knowledge of Data Governance and Data Quality frameworks.
  4. Experience building enterprise-scale cloud data platforms.

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