Senior Data Engineer (10+ years) to design and optimize enterprise data solutions using Microsoft Fa
Posted
S I Systems Senior Data Engineer (10+ years) to design and optimize enterprise data solutions using Microsoft Fa
Summary
Contract, hybrid role in Calgary (MST hours) for a senior data engineer to design, build, and optimize enterprise data pipelines using Microsoft Fabric and Azure Databricks, with SAP integration (S/4HANA, ECC, BW, Datasphere) as part of a large-scale data modernization program enabling analytics, reporting, and AI-driven capabilities. Placed by staffing firm S I Systems.
Senior Data Engineer (10+ years) to design and optimize enterprise data solutions using Microsoft Fabric, Azure Databricks, and SAP data integration
Our client is seeking a
Senior Data Engineer (10+ years) to design and optimize enterprise data solutions using Microsoft Fabric, Azure Databricks, and SAP data integration Join a large-scale enterprise data modernization initiative supporting analytics, reporting, operational insights, and AI-driven capabilities across multiple business functions. This role focuses on building scalable Microsoft Fabric and Azure Databricks data solutions integrated with SAP environments including Finance, Supply Chain, Asset Management, and Customer Operations. The consultant will contribute to enterprise-grade data products, SAP-to-Fabric ingestion pipelines, and modern cloud data architecture initiatives. Must Haves 10+ years in
Data Engineering
delivering large-scale
ETL/ELT
solutions 2+ years working with
Microsoft Fabric
in enterprise environments including OneLake and Fabric Data Factory 4+ years using
Azure Databricks ,
PySpark , and Spark SQL for large-scale data transformation SAP S/4HANA , SAP ECC, SAP BW, and SAP Datasphere data integration within enterprise analytics platforms Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, or related discipline Nice to Have Experience within utilities, energy, power generation, or oil & gas environments Experience with Asset Management data, Work Management systems, Customer Information Systems, or metering and operational technology data Experience integrating SCADA data, IoT data, or real-time streaming data Microsoft Fabric Certification, Azure Data Engineer Associate certification, or Databricks Certification Responsibilities Design, develop, and maintain scalable data pipelines within Microsoft Fabric Build enterprise data ingestion frameworks for structured and semi-structured data sources Develop and optimize ETL/ELT processes utilizing Azure Databricks, PySpark, Spark SQL, and Python Build and maintain integration pipelines extracting data from SAP S/4HANA, SAP ECC, SAP BW/BW4HANA, SAP Datasphere, and SAP SuccessFactors Design and build Fabric-based data products supporting self-service analytics, enterprise reporting, executive dashboards, and predictive analytics initiatives Implement data quality controls, metadata management, data lineage, and data cataloging processes Support CI/CD deployment processes, monitor pipeline performance, and troubleshoot production issues Our client is seeking a
Senior Data Engineer (10+ years) to design and optimize enterprise data solutions using Microsoft Fabric, Azure Databricks, and SAP data integration Join a large-scale enterprise data modernization initiative supporting analytics, reporting, operational insights, and AI-driven capabilities across multiple business functions. This role focuses on building scalable Microsoft Fabric and Azure Databricks data solutions integrated with SAP environments including Finance, Supply Chain, Asset Management, and Customer Operations. The consultant will contribute to enterprise-grade data products, SAP-to-Fabric ingestion pipelines, and modern cloud data architecture initiatives. Contract, Calgary, Hybrid, Working Hours: MST Must Haves 10+ years in
Data Engineering
delivering large-scale
ETL/ELT
solutions 2+ years working with
Microsoft Fabric
in enterprise environments including OneLake and Fabric Data Factory 4+ years using
Azure Databricks ,
PySpark , and Spark SQL for large-scale data transformation SAP S/4HANA , SAP ECC, SAP BW, and SAP Datasphere data integration within enterprise analytics platforms Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, or related discipline Nice to Have Experience within utilities, energy, power generation, or oil & gas environments Experience with Asset Management data, Work Management systems, Customer Information Systems, or metering and operational technology data Experience integrating SCADA data, IoT data, or real-time streaming data Microsoft Fabric Certification, Azure Data Engineer Associate certification, or Databricks Certification Responsibilities Design, develop, and maintain scalable data pipelines within Microsoft Fabric Build enterprise data ingestion frameworks for structured and semi-structured data sources Develop and optimize ETL/ELT processes utilizing Azure Databricks, PySpark, Spark SQL, and Python Build and maintain integration pipelines extracting data from SAP S/4HANA, SAP ECC, SAP BW/BW4HANA, SAP Datasphere, and SAP SuccessFactors Design and build Fabric-based data products supporting self-service analytics, enterprise reporting, executive dashboards, and predictive analytics initiatives Implement data quality controls, metadata management, data lineage, and data cataloging processes Support CI/CD deployment processes, monitor pipeline performance, and troubleshoot production issues Disclaimer: AI may be used in evaluating candidates. This posting is for an existing vacancy.
Our client is seeking a
Senior Data Engineer (10+ years) to design and optimize enterprise data solutions using Microsoft Fabric, Azure Databricks, and SAP data integration Join a large-scale enterprise data modernization initiative supporting analytics, reporting, operational insights, and AI-driven capabilities across multiple business functions. This role focuses on building scalable Microsoft Fabric and Azure Databricks data solutions integrated with SAP environments including Finance, Supply Chain, Asset Management, and Customer Operations. The consultant will contribute to enterprise-grade data products, SAP-to-Fabric ingestion pipelines, and modern cloud data architecture initiatives. Must Haves 10+ years in
Data Engineering
delivering large-scale
ETL/ELT
solutions 2+ years working with
Microsoft Fabric
in enterprise environments including OneLake and Fabric Data Factory 4+ years using
Azure Databricks ,
PySpark , and Spark SQL for large-scale data transformation SAP S/4HANA , SAP ECC, SAP BW, and SAP Datasphere data integration within enterprise analytics platforms Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, or related discipline Nice to Have Experience within utilities, energy, power generation, or oil & gas environments Experience with Asset Management data, Work Management systems, Customer Information Systems, or metering and operational technology data Experience integrating SCADA data, IoT data, or real-time streaming data Microsoft Fabric Certification, Azure Data Engineer Associate certification, or Databricks Certification Responsibilities Design, develop, and maintain scalable data pipelines within Microsoft Fabric Build enterprise data ingestion frameworks for structured and semi-structured data sources Develop and optimize ETL/ELT processes utilizing Azure Databricks, PySpark, Spark SQL, and Python Build and maintain integration pipelines extracting data from SAP S/4HANA, SAP ECC, SAP BW/BW4HANA, SAP Datasphere, and SAP SuccessFactors Design and build Fabric-based data products supporting self-service analytics, enterprise reporting, executive dashboards, and predictive analytics initiatives Implement data quality controls, metadata management, data lineage, and data cataloging processes Support CI/CD deployment processes, monitor pipeline performance, and troubleshoot production issues Our client is seeking a
Senior Data Engineer (10+ years) to design and optimize enterprise data solutions using Microsoft Fabric, Azure Databricks, and SAP data integration Join a large-scale enterprise data modernization initiative supporting analytics, reporting, operational insights, and AI-driven capabilities across multiple business functions. This role focuses on building scalable Microsoft Fabric and Azure Databricks data solutions integrated with SAP environments including Finance, Supply Chain, Asset Management, and Customer Operations. The consultant will contribute to enterprise-grade data products, SAP-to-Fabric ingestion pipelines, and modern cloud data architecture initiatives. Contract, Calgary, Hybrid, Working Hours: MST Must Haves 10+ years in
Data Engineering
delivering large-scale
ETL/ELT
solutions 2+ years working with
Microsoft Fabric
in enterprise environments including OneLake and Fabric Data Factory 4+ years using
Azure Databricks ,
PySpark , and Spark SQL for large-scale data transformation SAP S/4HANA , SAP ECC, SAP BW, and SAP Datasphere data integration within enterprise analytics platforms Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, or related discipline Nice to Have Experience within utilities, energy, power generation, or oil & gas environments Experience with Asset Management data, Work Management systems, Customer Information Systems, or metering and operational technology data Experience integrating SCADA data, IoT data, or real-time streaming data Microsoft Fabric Certification, Azure Data Engineer Associate certification, or Databricks Certification Responsibilities Design, develop, and maintain scalable data pipelines within Microsoft Fabric Build enterprise data ingestion frameworks for structured and semi-structured data sources Develop and optimize ETL/ELT processes utilizing Azure Databricks, PySpark, Spark SQL, and Python Build and maintain integration pipelines extracting data from SAP S/4HANA, SAP ECC, SAP BW/BW4HANA, SAP Datasphere, and SAP SuccessFactors Design and build Fabric-based data products supporting self-service analytics, enterprise reporting, executive dashboards, and predictive analytics initiatives Implement data quality controls, metadata management, data lineage, and data cataloging processes Support CI/CD deployment processes, monitor pipeline performance, and troubleshoot production issues Disclaimer: AI may be used in evaluating candidates. This posting is for an existing vacancy.