Sr. Database Engineer (Only W2)

Overview

We are seeking an experienced Sr. Database Engineer (contractor) to design, build, and optimize complex data systems. This senior-level contractor will work across multiple domains including data architecture, pipeline development, and system operations.

Key Responsibilities

• Design and implement scalable and reliable data architectures that support large-scale data processing, transformation, and analysis.
• Develop, maintain, and optimize ETL/ELT pipelines using modern tools and frameworks to move and transform data from diverse sources (flat files, streaming systems, REST APIs, EHRs, etc.).
• Build and support high-performance, cloud-based systems for real-time and batch processing (e.g., data lakes, warehouses, and mesh architectures).
• Collaborate with stakeholders across engineering, data science, and product teams to gather requirements and deliver actionable data solutions.
• Interface with Electronic Health Records (EHR) and healthcare data formats to ensure integration accuracy and compliance.
• Own operational excellence for data systems including logging, monitoring, alerting, and incident response.
• Utilize advanced programming skills (.NET, Java, or similar) and SQL to engineer robust data services.
• Contribute to architecture frameworks and documentation to guide team standards and best practices.
• Act as a subject matter expert (SME), mentoring junior engineers and promoting engineering excellence across the organization.

Qualifications

• 7 10+ years of professional experience in data engineering, software development, or database systems.
• Proven experience with SSIS and ADF.
• **Bachelor's degree in Computer Science, Engineering, or related field or equivalent experience.
• Expertise in SQL, database systems, and modern data processing tools and frameworks.
• Strong proficiency in at least one programming language (.NET, Java, Python, etc.).
• Demonstrated experience with modern cloud platforms (Azure, AWS, or Google Cloud Platform).
• Familiarity with data streaming and queuing technologies (Kafka, SNS, RabbitMQ, etc.).
• Understanding of CI/CD pipelines, infrastructure-as-code (Terraform), and containerized deployments (e.g., Kubernetes).
• Comfortable with production system support, debugging, and performance optimization.
• Strong problem-solving, communication, and collaboration skills.
• High-level understanding of big data design patterns and architectural principles (e.g., data lake vs. warehouse vs. mesh).
• Experience with RESTful APIs and integrating external data sources into internal systems.