Data Engineer

Role & responsibilities

Responsibilities

• Develop, maintain, test, and optimize Azure SQL Database objects, including tables, views, stored procedures, functions, and complex queries.
• Design, build, deploy, monitor, and support Azure Data Factory pipelines for data ingestion, transformation, movement, and orchestration.
• Develop and maintain ETL/ELT processes that integrate data from multiple source systems into enterprise reporting and analytics platforms.
• Troubleshoot production data issues, pipeline failures, performance problems, and data quality concerns in a timely and methodical manner.
• Perform root cause analysis, document findings, and implement durable solutions that improve platform reliability and prevent recurring incidents.
• Monitor data pipelines, database workloads, and operational processes; identify opportunities to improve performance, scalability, and supportability.
• Deliver trusted and governed datasets for enterprise reporting, analytics, and downstream business processes.
• Participate in data warehouse development using Kimball dimensional modeling principles.
• Develop and maintain fact tables, dimension tables, surrogate keys, and star schema relationships.
• Collaborate with business stakeholders to gather requirements, clarify data definitions, and translate business needs into practical technical solutions.
• Partner with the Data Architect and other technical team members on data models, solution designs, integration patterns, and development standards.
• Create and maintain technical specifications, source-to-target mappings, data flow documentation, runbooks, and operational procedures, as required.
• Participate in code reviews, peer testing, release activities, and continuous improvement of development practices.
• Follow established security, data governance, change management, and production support procedures.
• Provide operational support for data platform changes and critical incidents, including occasional off-hours support when business impact requires it.

Skills

• Advanced SQL development, query optimization, indexing, and execution plan analysis.
• Azure SQL Database administration fundamentals, including security, monitoring, performance, and deployment considerations.
• Azure Data Factory development, parameterization, triggers, integration runtimes, monitoring, and troubleshooting.
• Kimball dimensional modeling methodology; fact, dimension, and star schema design.
• ETL/ELT patterns, incremental loading, data validation, error handling, and logging.
• Data quality, governance, auditability, and operational control concepts.
• General awareness of Git-based development, Microsoft Fabric, Power BI, and CI/CD processes.

Qualifications

• 4 years minimum of professional experience in data engineering, database development, business intelligence engineering, or a closely related role.
• Strong hands-on SQL development experience, including complex queries, stored procedures, views, functions, and performance tuning.
• Experience developing and supporting solutions in Azure SQL Database.
• Experience building, deploying, monitoring, and troubleshooting Azure Data Factory pipelines.
• Experience developing ETL/ELT workflows and integrating data from multiple source systems.
• Working knowledge of data warehousing concepts, dimensional modeling, and star schema design.
• Experience supporting production data systems and resolving operational incidents.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to manage assigned development and support work with appropriate urgency, accuracy, and follow-through.
• Excellent written and verbal communication skills, with the ability to work effectively with technical and non-technical stakeholders.

Education/Certifications (Preferred)

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field; equivalent practical experience will be considered.
• Relevant Microsoft certifications in Azure, data engineering, database development, Fabric, or Power BI are preferred but not required.
• Experience using a source control platform in a team-based development environment.
• Experience with Microsoft Fabric, including data pipelines, lakehouses, warehouses, or related data engineering capabilities.
• Experience supporting Power BI semantic models.
• Relevant Microsoft Azure or data engineering certifications are a plus.

Physical Requirements

• Ability to work in a remote work environment for extended periods of time
• Prolonged periods of sitting while working at a computer and using multiple monitors
• Regular use of hands, fingers, and vision for keyboarding, reviewing technical documentation, dashboards, and diagrams
• Ability to participate in extended meetings via video or phone conferencing