Azure Data Engineer

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.