Job Summary

Senior Data Engineer

Positions required: 4

Purpose

Own end-to-end technical delivery for an assigned set of PowerCenter and/or SAP BW use cases — design and build the target Fabric logic, and act as the technical escalation point for the Data Engineers working under them.

Responsibilities

• Convert PowerCenter mappings/workflows into maintainable Fabric Warehouse T-SQL (stored procedures, functions, views) and orchestrate via Fabric Data Pipelines.
• Convert SAP BW ABAP transformation logic (Bronze → Silver → Gold) to PySpark/T-SQL on Fabric, one-to-one, with no redesign of the existing data model or business logic.
• Build and review ADF copy activities / Fabric pipelines extracting from HANA DB, MS-SQL and ADLS (CSV, delta Parquet) sources.
• Implement row-level and column-level security (RLS/CLS) in Synapse serverless views per Achmea's existing per-consumer split pattern, including long-retention (50+ year) object handling.
• Lead technical design and conversion for the highest-complexity use cases (the top complexity tier).
• Produce readable, documented T-SQL/PySpark that passes Achmea developer code review.
• Support shadow-run validation and performance benchmarking (run-log comparison) against the legacy PowerCenter/SAP BW systems.
• Mentor and review the work of Data Engineers; triage and resolve defects escalated from Tester/Reconciliation.

Required Skills & Experience

• 8+ years hands-on data engineering, with production experience in Informatica PowerCenter (mappings, workflows, mapplets) and/or SAP BW/ABAP (extractors, DSOs/ADSOs, transformations, process chains, DTPs).
• Strong T-SQL and PySpark development, ideally on Microsoft Fabric (Warehouse, Lakehouse, Notebooks) or an equivalent modern Azure data platform (Synapse, Databricks).
• Experience with Azure Data Factory / Fabric Data Pipelines and ADLS Gen2.
• Working knowledge of SAP extraction patterns (ODP, SAP Premium Outbound Interface / Datasphere) is an advantage.
• Exposure to AI-assisted code-conversion accelerators, and awareness of EEA data-residency and AI Act constraints, is a strong plus.
• Comfortable working within a capped Time & Materials model and a blended onshore/nearshore/offshore delivery team.
• Mandatory technical stack: Cloud (Azure), Microsoft Fabric or Synapse, T-SQL, PySpark.

Key Responsibilities

Senior Data Engineer

Positions required: 4

Purpose

Own end-to-end technical delivery for an assigned set of PowerCenter and/or SAP BW use cases — design and build the target Fabric logic, and act as the technical escalation point for the Data Engineers working under them.

Responsibilities

• Convert PowerCenter mappings/workflows into maintainable Fabric Warehouse T-SQL (stored procedures, functions, views) and orchestrate via Fabric Data Pipelines.
• Convert SAP BW ABAP transformation logic (Bronze → Silver → Gold) to PySpark/T-SQL on Fabric, one-to-one, with no redesign of the existing data model or business logic.
• Build and review ADF copy activities / Fabric pipelines extracting from HANA DB, MS-SQL and ADLS (CSV, delta Parquet) sources.
• Implement row-level and column-level security (RLS/CLS) in Synapse serverless views per Achmea's existing per-consumer split pattern, including long-retention (50+ year) object handling.
• Lead technical design and conversion for the highest-complexity use cases (the top complexity tier).
• Produce readable, documented T-SQL/PySpark that passes Achmea developer code review.
• Support shadow-run validation and performance benchmarking (run-log comparison) against the legacy PowerCenter/SAP BW systems.
• Mentor and review the work of Data Engineers; triage and resolve defects escalated from Tester/Reconciliation.

Required Skills & Experience

• 8+ years hands-on data engineering, with production experience in Informatica PowerCenter (mappings, workflows, mapplets) and/or SAP BW/ABAP (extractors, DSOs/ADSOs, transformations, process chains, DTPs).
• Strong T-SQL and PySpark development, ideally on Microsoft Fabric (Warehouse, Lakehouse, Notebooks) or an equivalent modern Azure data platform (Synapse, Databricks).
• Experience with Azure Data Factory / Fabric Data Pipelines and ADLS Gen2.
• Working knowledge of SAP extraction patterns (ODP, SAP Premium Outbound Interface / Datasphere) is an advantage.
• Exposure to AI-assisted code-conversion accelerators, and awareness of EEA data-residency and AI Act constraints, is a strong plus.
• Comfortable working within a capped Time & Materials model and a blended onshore/nearshore/offshore delivery team.
• Mandatory technical stack: Cloud (Azure), Microsoft Fabric or Synapse, T-SQL, PySpark.

Skill Requirements

Senior Data Engineer

Positions required: 4

Purpose

Own end-to-end technical delivery for an assigned set of PowerCenter and/or SAP BW use cases — design and build the target Fabric logic, and act as the technical escalation point for the Data Engineers working under them.

Responsibilities

• Convert PowerCenter mappings/workflows into maintainable Fabric Warehouse T-SQL (stored procedures, functions, views) and orchestrate via Fabric Data Pipelines.
• Convert SAP BW ABAP transformation logic (Bronze → Silver → Gold) to PySpark/T-SQL on Fabric, one-to-one, with no redesign of the existing data model or business logic.
• Build and review ADF copy activities / Fabric pipelines extracting from HANA DB, MS-SQL and ADLS (CSV, delta Parquet) sources.
• Implement row-level and column-level security (RLS/CLS) in Synapse serverless views per Achmea's existing per-consumer split pattern, including long-retention (50+ year) object handling.
• Lead technical design and conversion for the highest-complexity use cases (the top complexity tier).
• Produce readable, documented T-SQL/PySpark that passes Achmea developer code review.
• Support shadow-run validation and performance benchmarking (run-log comparison) against the legacy PowerCenter/SAP BW systems.
• Mentor and review the work of Data Engineers; triage and resolve defects escalated from Tester/Reconciliation.

Required Skills & Experience

• 8+ years hands-on data engineering, with production experience in Informatica PowerCenter (mappings, workflows, mapplets) and/or SAP BW/ABAP (extractors, DSOs/ADSOs, transformations, process chains, DTPs).
• Strong T-SQL and PySpark development, ideally on Microsoft Fabric (Warehouse, Lakehouse, Notebooks) or an equivalent modern Azure data platform (Synapse, Databricks).
• Experience with Azure Data Factory / Fabric Data Pipelines and ADLS Gen2.
• Working knowledge of SAP extraction patterns (ODP, SAP Premium Outbound Interface / Datasphere) is an advantage.
• Exposure to AI-assisted code-conversion accelerators, and awareness of EEA data-residency and AI Act constraints, is a strong plus.
• Comfortable working within a capped Time & Materials model and a blended onshore/nearshore/offshore delivery team.
• Mandatory technical stack: Cloud (Azure), Microsoft Fabric or Synapse, T-SQL, PySpark.

Other Requirements

Senior Data Engineer

Positions required: 4

Purpose

Own end-to-end technical delivery for an assigned set of PowerCenter and/or SAP BW use cases — design and build the target Fabric logic, and act as the technical escalation point for the Data Engineers working under them.

Responsibilities

• Convert PowerCenter mappings/workflows into maintainable Fabric Warehouse T-SQL (stored procedures, functions, views) and orchestrate via Fabric Data Pipelines.
• Convert SAP BW ABAP transformation logic (Bronze → Silver → Gold) to PySpark/T-SQL on Fabric, one-to-one, with no redesign of the existing data model or business logic.
• Build and review ADF copy activities / Fabric pipelines extracting from HANA DB, MS-SQL and ADLS (CSV, delta Parquet) sources.
• Implement row-level and column-level security (RLS/CLS) in Synapse serverless views per Achmea's existing per-consumer split pattern, including long-retention (50+ year) object handling.
• Lead technical design and conversion for the highest-complexity use cases (the top complexity tier).
• Produce readable, documented T-SQL/PySpark that passes Achmea developer code review.
• Support shadow-run validation and performance benchmarking (run-log comparison) against the legacy PowerCenter/SAP BW systems.
• Mentor and review the work of Data Engineers; triage and resolve defects escalated from Tester/Reconciliation.

Required Skills & Experience

• 8+ years hands-on data engineering, with production experience in Informatica PowerCenter (mappings, workflows, mapplets) and/or SAP BW/ABAP (extractors, DSOs/ADSOs, transformations, process chains, DTPs).
• Strong T-SQL and PySpark development, ideally on Microsoft Fabric (Warehouse, Lakehouse, Notebooks) or an equivalent modern Azure data platform (Synapse, Databricks).
• Experience with Azure Data Factory / Fabric Data Pipelines and ADLS Gen2.
• Working knowledge of SAP extraction patterns (ODP, SAP Premium Outbound Interface / Datasphere) is an advantage.
• Exposure to AI-assisted code-conversion accelerators, and awareness of EEA data-residency and AI Act constraints, is a strong plus.
• Comfortable working within a capped Time & Materials model and a blended onshore/nearshore/offshore delivery team.
• Mandatory technical stack: Cloud (Azure), Microsoft Fabric or Synapse, T-SQL, PySpark.