Design and optimize enterprise data models and pipelines integrating SAP Core, PostgreSQL, MySQL and legacy systems. Implement data cataloging, lineage and metadata management. Tune SQL and database performance, build ETL/ELT pipelines, and collaborate with architects and global teams to deliver scalable data architecture for a new strategic initiative.
Job Title: Senior Data Engineer (Data Modeling & Multi-Source Integration)
Experience: 5 – 8 Years
Position Overview
Zealogics Technologies is seeking an experienced and analytical Senior Data Engineer (5–8 years) to architect, model, and optimize the foundational data infrastructure for a brand-new strategic project. This role requires deep expertise in establishing relationships across heterogeneous data sources (SAP Core, PostgreSQL, MySQL), building comprehensive data catalogs/lineage, and fine-tuning high-performance data pipelines.
Key Responsibilities
Experience: 5 – 8 Years
Position Overview
Zealogics Technologies is seeking an experienced and analytical Senior Data Engineer (5–8 years) to architect, model, and optimize the foundational data infrastructure for a brand-new strategic project. This role requires deep expertise in establishing relationships across heterogeneous data sources (SAP Core, PostgreSQL, MySQL), building comprehensive data catalogs/lineage, and fine-tuning high-performance data pipelines.
Key Responsibilities
- Data Modeling & Relationship Mapping: Architect conceptual, logical, and physical data models for a new enterprise solution. Identify, map, and resolve complex entity relationships across SAP Core, PostgreSQL, MySQL, and legacy systems.
- Data Lineage & Cataloging: Implement enterprise data cataloging, metadata tracking, and end-to-end data lineage to ensure visibility, governance, and auditability across all data layers.
- Performance Optimization & Tuning: Analyze execution plans, optimize complex SQL queries, fine-tune database configurations, indexing, and partitioning to ensure high throughput and minimal latency.
- Document & Unstructured Metadata Management (Advantageous): Design and maintain robust metadata indexing mechanisms for large-scale document management systems (e.g., In-house DMS, Azure Blob Storage).
- Pipeline Engineering: Build reliable ETL/ELT data pipelines integrating structured, semi-structured, and enterprise data repositories into a unified system.
- Cross-Functional Collaboration: Partner with enterprise architects, product owners, and global client technical teams to translate business requirements into scalable data architectures.
- Experience: 5–8 years of dedicated hands-on experience in Data Engineering, Data Architecture, and Enterprise Data Modeling.
- Data Modeling Mastery: Proven expertise in dimensional modeling, Data Vault, ER diagrams, and multi-source relationship mapping.
- Heterogeneous Databases: Solid expertise in working with SAP Core, PostgreSQL, and MySQL.
- Governance & Lineage: Experience with modern data cataloging and lineage tools (e.g., OpenMetadata, Apache Atlas, Microsoft Purview, Collibra, or dbt docs).
- Performance Tuning: Expert knowledge in SQL optimization, indexing strategies, memory tuning, and query troubleshooting.
- Cloud & Modern Data Stack: Hands-on experience with cloud ecosystems (Azure/AWS) and pipeline orchestration tools (Spark, Databricks, dbt, Airflow, etc.).
- Strong verbal and professional communication skills to deal with architects & data engineers across globe.
- Proven ability to extract, index, and manage metadata for large enterprise document repositories (In-house DMS, Azure Blob Storage, S3).
- Exposure to OCR/document metadata workflows and semi-structured cataloging.
- Prior experience delivering high-impact solutions for global clients and internal products.
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