Data Engineer

Our client, a top healthcare company, seeks a Data Engineering with 5 to 7 years of relevant experience, who excels at designing, building, and optimizing scalable data architectures and processes to enable efficient data utilization and data-driven decision-making. The ideal candidate will combine deep technical expertise with strong leadership skills to deliver best-in-class data engineering solutions, drive process improvements, and mentor junior team members in a high-performing environment. This is a contractual position through the end of 2026. The client prefers that the candidate to be nearby the greater San Francisco area, but they will consider all profiles from the Pacific and Mountain time zones. The Role. • Design and implementation of robust, scalable, and high-performance data systems that align with organizational goals. • Collaborate with cross-functional stakeholders to understand data requirements and translate them into effective architecture and engineering solutions. • Develop and manage software processes enabling seamless data movement across data warehouses, data lakes, and internal systems. • Design and optimize ETL (Extract, Transform, Load) pipelines to prepare high-quality, reliable data for various stakeholders. • Build and maintain data ingestion frameworks, data quality controls, and integrated audit systems. • Implement and uphold data governance practices to ensure data accuracy, integrity, and security. • Perform data analysis and communicate findings and actionable insights to business and technical teams. • Drive continuous improvement in data engineering processes, standards, and team capabilities. • Support collaboration across technical and business units to promote a data-driven culture. Requirements • Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field. • 5 years (max 7 years) of hands-on experience in data engineering with a proven track record of designing and implementing scalable, high-performance data systems. • Proficiency in DBT, Python, PySpark, Redshift, Snowflake, and Talend for ETL and data pipeline development. • Strong understanding of data warehousing concepts and cloud-based data platforms (AWS). • Expertise in ETL design, data modelling, and database management. • Strong problem-solving, analytical, and critical-thinking abilities. • Excellent communication and collaboration skills, with the ability to work across business and technical functions. Preferred Qualifications. • Experience working in healthcare data ecosystems or regulated industries. • AWS Data Analytics or Solutions Architect certification. • Knowledge of DevOps and CI/CD practices for data engineering. • Familiarity with data governance frameworks and compliance standards (HIPAA, PHI).