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 skilled 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.

📌 Azure Data Engineer (Kochi)
🏢 BRIDGE Global
📍 Kochi