We are seeking a highly skilled and experienced Senior Data Engineer to join our team. This role will be instrumental in designing, developing, and maintaining our data infrastructure, ensuring the effective processing and analysis of large datasets. The ideal candidate will have a strong background in data modeling, data architecture, and experience with a variety of data technologies. Key Responsibilities: Design and implement robust data pipelines, ETL processes, and data warehouses to support our analytics and reporting needs. Develop and maintain data models, schemas, and metadata to ensure data quality and consistency. Collaborate with data scientists, analysts, and business stakeholders to understand their requirements and translate them into technical solutions. Optimize data pipelines for performance and scalability to handle large volumes of data. Stay up-to-date with the latest data technologies and trends to drive innovation and efficiency. Responsibilities Design, develop, and maintain scalable data architectures, pipelines, APIs, and integrations. Create and optimize data models to support efficient data processing and storage. Manage and maintain databases, including Postgres, SSIS, ensuring data integrity and performance. Develop, deploy, and manage ETL and EDI processes. Develop and maintain scripts and applications using Python for data processing and analysis. Ensure data security and compliance with relevant regulations and best practices. Leverage cloud services (e.g., Azure, AWS) for data storage, processing, and analytics. Collaborate with cross-functional teams to gather requirements and provide data-driven insights. Implement and manage caching solutions to improve data retrieval speeds. Create and maintain comprehensive documentation for all data processes and architectures. Utilize data visualization tools to create interactive dashboards and reports for stakeholders. Qualifications Bachelors degree in Computer Science, Information Systems, Data Science, or a related field (or equivalent work experience). Minimum of 5 years of experience in data engineering or a related field. Proficiency in data modeling, data architecture, and database management with Postgres or SSIS.. Experience with electronic medical records (EMRs) and understanding of the healthcare industry is strongly desired. Strong SQL skills and experience with common ETL tools. Proficiency in Python for data processing and automation. Experience with common caching solutions (e.g., Redis, Memcached). Expertise in data security best practices and regulatory compliance. Hands-on experience with cloud platforms like Azure and AWS. Proficiency with data visualization tools such as Power BI, Tableau, or similar. Excellent problem-solving skills and ability to troubleshoot data issues effectively. Strong communication skills, both written and verbal, with the ability to explain complex technical concepts to non-technical stakeholders. Desired Skills Knowledge of data warehousing concepts and methodologies. Experience with Agile/Scrum methodologies. Familiarity with Power BI administration and deployment.

Strategic Leadership & Vision: Define and execute the technical strategy and roadmap for our SaaS platform, aligning with overall business objectives and product vision. Collaborate with Product Management, Sales, and Customer Success to understand market needs and translate them into actionable engineering plans. Identify and evaluate new technologies, tools, and methodologies to enhance our development processes and product capabilities. Team Leadership & Management: Lead, mentor, and grow multiple engineering teams, fostering a collaborative, inclusive, and high-performing environment. Oversee recruiting, hiring, and retention of top engineering talent. Conduct performance reviews, provide regular feedback, and support the professional development of team members. Promote engineering best practices, code quality, testing methodologies, and architectural standards. SaaS Development & Delivery: Oversee the end-to-end software development lifecycle (SDLC) for our SaaS products, from conceptualization to deployment and post-launch support. Ensure the timely delivery of high-quality, scalable, secure, and reliable software releases. Drive adoption of agile methodologies (Scrum/Kanban) and continuous integration/continuous delivery (CI/CD) practices. Manage technical debt and ensure the long-term maintainability and extensibility of the codebase. Operational Excellence & Reliability: Ensure the 24/7 availability, performance, and security of our SaaS platform. Implement robust monitoring, logging, and alerting systems. Oversee incident management, root cause analysis, and preventative measures to minimize downtime. Manage cloud infrastructure (e.g., AWS, Azure, GCP) costs and optimization. Cross-functional Collaboration: Act as a key liaison between engineering and other departments, effectively communicating technical strategies and progress. Drive cross-functional initiatives to improve overall product delivery and customer satisfaction.