Back
Remote, generalist Data Engineer title and mid-level (5–8y) experience increase candidate competition.
Enterprise SAP integration, metadata and document-repository experience require domain-specific background, reducing transferability.
Explicit 5–8 years plus mandatory SAP, database, cloud and pipeline tooling requirements make shortlisting strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Architect and optimize data infrastructure including conceptual, logical, and physical data models for a new enterprise project.
Establish and resolve complex entity relationships across heterogeneous data sources such as SAP Core, PostgreSQL, and MySQL.
Implement enterprise data cataloging and lineage systems, optimize SQL queries and database performance, and build reliable ETL/ELT pipelines.
5–8 years of hands-on experience in Data Engineering, Data Architecture, and Enterprise Data Modeling.
Strong expertise in data modeling techniques including dimensional modeling, Data Vault, and ER diagrams.
Proficiency in working with SAP Core, PostgreSQL, and MySQL databases.
Experience with data cataloging and lineage tools (e.g., OpenMetadata, Apache Atlas, Microsoft Purview), and performance tuning of SQL queries.
Experience collaborating with enterprise architects and global client technical teams to translate business requirements into scalable architectures.
Proven ability to handle multi-source data integration and optimize pipelines using cloud environments such as Azure or AWS and orchestration tools like Spark, Databricks, dbt, or Airflow.
Familiarity with metadata management for large enterprise document repositories and knowledge of document indexing or semi-structured data workflows.