Senior Data Engineer

Job Summary: We are seeking a Senior Data Engineer to design, build, and optimize scalable data platforms and pipelines that power analytics, reporting, and data-driven decision-making. This is a highly technical, hands-on role focused on data architecture, performance, reliability, and security across relational, NoSQL, and cloud-native storage systems. The ideal candidate brings deep experience in data engineering and software development and leads primarily through technical ownership and influence. Key Responsibilities: • Design, develop, and maintain scalable data pipelines and architectures using SQL Server, Azure Databricks, Azure Cosmos DB, and Azure Blob Storage. • Build and optimize ETL/ELT workflows to ingest data from transactional systems, APIs, and streaming sources into analytical data stores. • Develop and maintain data models for both relational (SQL Server, Snowflake) and NoSQL platforms (Cosmos DB), optimized for performance and analytical use cases. • Implement data quality, validation, and monitoring frameworks to ensure accuracy, reliability, and observability across pipelines. • Optimize query performance, indexing strategies, partitioning, and storage costs across SQL Server and cloud data platforms. • Implement and enforce data security and compliance best practices, including role- based access control, encryption, and secure data handling. • Collaborate with analytics, application, and platform engineering teams to translate business requirements into robust technical solutions. • Build and maintain orchestration workflows using tools such as Azure Data Factory and Apache Airflow. • Support CI/CD pipelines for data solutions, including version control, automated testing, and deployment. • Evaluate and adopt new data technologies and patterns to continuously improve platform scalability and resilience. • Provide technical guidance and mentorship through code reviews, design discussions, and best-practice advocacy. Qualifications: • Bachelor’s degree in computer science, Engineering, or a related field. • 12+ years of experience in software development, with substantial hands-on experience in data engineering. • Strong expertise in SQL Server, including schema design, performance tuning, indexing, and stored procedures. • Hands-on experience with Azure Cosmos DB (data modeling, partitioning, throughput optimization). • Experience working with Azure Blob Storage and cloud-based data lakes. • Proficiency with Databricks, NoSQL databases (Cosmos DB, MongoDB, DynamoDB), and distributed data processing. • Deep understanding of ETL/ELT, data warehousing, and data modeling concepts. • Experience with cloud platforms, primarily Azure (AWS exposure a plus). • Hands-on experience with data pipeline orchestration tools such as Azure Data Factory or Apache Airflow. • Strong problem-solving skills and attention to detail, with a focus on scalability and reliability. • Ability to clearly communicate technical concepts to both technical and non- technical stakeholders. Preferred Qualifications: • Experience preparing and serving data for machine learning and advanced analytics use cases. • Background in building and operating large-scale, distributed data environments. • Experience working in Agile/Scrum teams. • Familiarity with data governance, lineage, and observability tools in regulated • environments.