Senior Data Engineer (Energy & Utilities – Data Migration Specialist)

Opportunity • We are seeking an experienced Senior Data Engineer with 10+ years of overall experience, including 5+ years of hands-on expertise delivering end-to-end data migration solutions within the Energy & Utilities domain. • This role requires strong technical capability in modern cloud data platforms, particularly Snowflake and the Microsoft Azure ecosystem, including Azure Data Factory, Azure DevOps, and Azure data platform services. The ideal candidate will bring deep experience in ETL/ELT delivery, SQL development, DataOps and CI/CD practices, and a strong understanding of CNI and SCADA domain data models. • The successful candidate will lead and assure data migration initiatives, ensuring solutions are scalable, secure, performant, governed, and aligned with enterprise standards and regulatory requirements. Required Skills & Experience • 10+ years of experience in data engineering, with at least 5 years in end-to-end data migration delivery. • Proven experience in the Energy & Utilities domain. • Strong hands-on expertise with Snowflake and Microsoft Azure data services. • Deep experience with Azure Data Factory (ADF), Azure DevOps, and dataops.live. • Strong proficiency in SQL, including complex transformations, reconciliation logic, and performance tuning. • Hands-on experience designing and delivering ETL/ELT pipelines in cloud environments. • Strong understanding of CNI and SCADA data models, telemetry data, and operational datasets. • Experience with batch and near real-time data ingestion architectures. • Solid knowledge of DataOps, CI/CD, automation, testing, and deployment governance. • Familiarity with data quality, metadata, lineage, cataloging, and compliance frameworks. • Ability to review, assure, and improve existing migration solutions in complex enterprise environments. Key Responsibilities Data Migration & Engineering • Review and assure existing data migration solutions to ensure they are scalable, secure, high-performing, and aligned with enterprise architecture standards. • Lead the end-to-end data migration lifecycle, including discovery, profiling, mapping, transformation, validation, reconciliation, and cutover. • Design, develop, and optimize ETL/ELT pipelines using Azure Data Factory, dataops.live, and other cloud-native tools. • Develop and tune complex SQL transformations for data ingestion, validation, reconciliation, and migration processing. • Ensure data accuracy, completeness, consistency, and traceability across all migration stages and environments. Cloud Data Platform Engineering • Build, optimize, and maintain data solutions on Snowflake and the Microsoft Azure platform. • Implement data ingestion pipelines for batch and near real-time processing using Azure-native services. • Design dimensional, canonical, and analytical data models aligned with business, operational, and regulatory requirements. • Optimize cloud data solutions for performance, scalability, resilience, and cost efficiency. DataOps, CI/CD & Automation • Implement DataOps best practices, including CI/CD pipelines, automated testing, deployment validation, and operational monitoring. • Use tools such as Azure DevOps, Git, dataops.live, and CI/CD frameworks to automate deployment and release processes for data pipelines. • Establish observability, logging, alerting, and proactive monitoring for ETL and data engineering workloads. • Promote repeatable, version-controlled, auditable, and automated delivery processes across data migration programs. Domain Expertise – Energy & Utilities • Work with complex datasets related to: • Asset and network management • Telemetry and SCADA data • CNI-grade datasets • Apply strong knowledge of Energy & Utilities data models, operational data landscapes, and regulatory constraints. • Ensure adherence to industry standards, compliance obligations, and regulatory frameworks throughout migration initiatives. Data Governance & Quality • Define and enforce data quality rules, controls, and validation frameworks. • Implement and support metadata management, data lineage, auditability, and data cataloging practices. • Collaborate with data governance, architecture, and security teams to ensure compliance with enterprise and regulatory data policies.