Data Engineer

Key Responsibilities: Data Engineering • Design, develop, and maintain ETL/ELT pipelines. • Build and support data ingestion frameworks. • Develop and maintain SQL-based data transformations. • Create and maintain operational and analytical datasets. • Support implementation of CDC (Change Data Capture) solutions. • Ensure data quality, consistency, and reliability across systems. • Troubleshoot production data issues and support root cause analysis. Database Development & Optimization • Develop complex SQL queries, stored procedures, functions, and views. • Review and optimize existing database objects. • Improve query performance and execution efficiency. • Implement indexing strategies and database optimization recommendations. • Support database migration and modernization initiatives. • Assist with backup, archival, retention, and purging activities. Analytics & Reporting Support • Support reporting and analytics platforms. • Create and maintain datasets used by dashboards and reporting solutions. • Collaborate with business and product teams to understand data requirements. • Support operational metrics, KPI reporting, and insights initiatives. Cloud & Integration • Develop and maintain Azure-based data solutions. • Support integrations between applications, APIs, and external systems. • Assist with implementation of Event Hubs, Synapse, Data Lake, and ClickHouse initiatives. • Work with application teams to support data exchange through APIs and microservices. Event & Streaming Platforms • Support event-driven data processing initiatives. • Develop and maintain CDC and event streaming pipelines. • Assist with telemetry and operational data collection initiatives. • Support Event Hub and analytical ingestion frameworks. Collaboration & Leadership • Provide technical guidance to Data Engineers and SQL Developers. • Participate in code reviews and knowledge-sharing sessions. • Support delivery planning and sprint execution. • Collaborate with Architects and Directors on implementation activities. • Work closely with Product, Engineering, QA, and DevOps teams. • Contribute to technical documentation and engineering standards. Qualifications: Required Experience 6-10 years of experience in Data Engineering, SQL Development, or Database Development. • Experience working in enterprise SaaS environments. • Experience mentoring developers or acting as a Technical Lead. • Experience working in Agile/Scrum teams. Technical Skills • SQL Server & Database Development: Microsoft SQL Server 2016/2019+, T-SQL, stored procedures, functions, views, query optimization, performance tuning, database design, data modelling, indexing strategies, execution plan analysis, transactions, and isolation levels. • Data Engineering: ETL/ELT development, data pipelines, data integration, data validation, data quality, data reconciliation, and CDC. • Cloud & Analytics: Azure SQL, Azure Data Lake, Azure Synapse, Azure Event Hubs, ClickHouse preferred, and Power BI preferred. • Integration: REST APIs, data exchange patterns, ServiceStack preferred, and event-driven processing preferred. • Programming: SQL, with C# and Python preferred. Good-to-Have Skills • Azure Data Factory • Azure Databricks • Event Hub Streaming • ClickHouse • NoSQL Databases • AI/ML Data Platforms • Semantic Search Platforms • Container-based Deployments