Senior Data Engineer

As a Senior Data Engineer, you will design, build, and tune the data layer that powers our clients' mission-critical applications on Azure and SQL Server. You will own complex query performance, indexing strategy, and concurrency design, and you will architect the data access patterns that connect application code to the database through linq2db, LINQ-to-SQL, Entity Framework, and ADO.NET. You will partner with application engineers, architects, and product teams to deliver high-throughput, low-latency data solutions, and you will mentor others on database design, query optimization, and modern data engineering practices. What qualifications make you an Aubrant Senior Data Engineer? A database craftsperson who treats query performance, indexing, and concurrency as first-class engineering concerns rather than afterthoughts. A clear communicator who can explain execution plans, locking behavior, and data access trade-offs to engineers, architects, and product stakeholders. Comfortable operating with ambiguity, capable of profiling production workloads and proposing concrete solutions backed by evidence. A mentor who raises the bar for the team through code review, query review, and pattern guidance. Customer-obsessed and outcome-focused, balancing delivery speed with the long-term health and scalability of the data platform. Responsibilities: Database Engineering & Performance: Design and maintain SQL Server 2019+ schemas, indexes, and query patterns that meet performance, scalability, and concurrency requirements. Analyze execution plans, identify bottlenecks, and tune queries, indexes, and statistics; advise on RCSI and isolation level choices. Design and operate Change Data Capture (CDC) pipelines and other change-tracking patterns to support downstream consumers. Data Access & Application Integration: Implement and review data access using linq2db, LINQ-to-SQL (DBML), Entity Framework, and ADO.NET; choose the right tool for each scenario. Translate business and application requirements into efficient SQL and C# data access code that is performant, testable, and maintainable. Partner with application engineers to align ORM usage with database performance characteristics and avoid common anti-patterns. Cloud Data Platform & Delivery: Design and operate data solutions on Azure, including Azure SQL, storage, networking, and security configurations. Contribute to CI/CD for database changes through migration scripts, schema versioning, and automated deployments. Mentor engineers on database design, query optimization, and data access patterns; set standards for the team. Qualifications: Bachelor's Degree in Computer Science or a related discipline, or equivalent experience; MUST be proficient in written and spoken English (85%). 5 to 8 years of professional data engineering or back-end engineering experience with a strong database focus. Expert-level proficiency in SQL on SQL Server 2019+, including complex queries, window functions, set-based operations, query plan analysis, indexing strategy, statistics, RCSI, isolation levels, and Change Data Capture. Expert-level proficiency in database performance tuning, including bottleneck identification, index design, query rewrites, and concurrency design under production load. Strong proficiency in C# data access using linq2db, LINQ-to-SQL (DBML), Entity Framework, and ADO.NET; ability to choose the appropriate tool for each scenario and avoid ORM performance pitfalls. Strong proficiency in Python for data engineering tasks, scripting, and automation. Hands-on experience with Azure data services (Azure SQL, storage, networking, security) and deploying production data workloads in Azure. Experience with database CI/CD, schema versioning, and migration tooling. Solid Git, code review discipline, and familiarity with modern engineering practices including testing and observability. Experience with Azure Data Factory, Synapse, or other Azure analytics services is a plus. Experience designing event-driven or streaming data architectures is a plus. Excellent analytical and problem-solving skills; strong communication, collaboration, customer orientation, innovation mindset, and adaptability under ambiguity.