Sr. Data Engineer

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 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 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 #J-18808-Ljbffr Anblicks