Data Engineer

Data Engineer Location: Remote / Hybrid (as applicable) Experience: 2+ Years Industry: Healthcare Analytics & Data Engineering About Optimus Health Analytics Optimus Health Analytics is building data-driven solutions that help healthcare organizations identify patients, improve engagement, optimize treatment, and drive better outcomes. We work with healthcare data across claims, EHRs, CCDA, HL7, and other interoperability standards to create trusted analytics and operational insights. We are seeking a Data Engineer who is passionate about building scalable data solutions and wants to make a meaningful impact in healthcare technology. What You’ll Do Data Engineering & Pipeline Development Design, build, test, and maintain scalable data pipelines using Python, SQL, and AWS technologies. Develop ETL and ELT processes to ingest and transform healthcare data from claims, EHRs, CCDA, HL7, APIs, and partner data feeds. Improve pipeline performance, reliability, monitoring, and error handling. Automate repeatable workflows and contribute to CI/CD best practices. Data Architecture & Modeling Build and maintain analytics-ready datasets, enterprise data models, and reporting structures. Support the evolution of our cloud-based data warehouse and data lake environments. Partner with engineering, analytics, and DevOps teams to improve scalability and accessibility of data assets. Data Quality, Governance & Security Implement validation, reconciliation, and monitoring controls to ensure high-quality data. Maintain documentation, data lineage, metadata, and operational procedures. Support HIPAA‑compliant handling of protected health information (PHI) and healthcare data governance standards. Collaboration Work closely with Analytics, Data Science, Product, Operations, and client-facing teams. Collaborate with healthcare partners to define data mappings, file specifications, onboarding requirements, and validation processes. Support machine learning and advanced analytics initiatives through the delivery of trusted datasets and production‑ready workflows. Required Qualifications 2+ years of experience in Data Engineering, Analytics Engineering, ETL Development, or a related role. Strong proficiency in Python and SQL. Experience building and maintaining ETL/ELT pipelines. Understanding of data modeling, data warehousing concepts, and relational databases. Experience working in Linux or Unix environments. Strong troubleshooting, problem-solving, and communication skills. High attention to detail with a focus on data quality and production reliability. Preferred Qualifications Experience working with healthcare data, including payer, provider, claims, clinical, quality, risk adjustment, or care management datasets. Familiarity with healthcare interoperability standards such as FHIR, CCDA, HL7, XML, and JSON. Experience with AWS services such as S3, Redshift, Glue, Lambda, Athena, IAM, and CloudWatch. Experience with workflow orchestration tools such as Apache Airflow. Knowledge of healthcare compliance and governance frameworks including HIPAA and NCQA. Experience supporting analytics engineering, machine learning pipelines, or feature engineering workflows. What Success Looks Like Reliable, scalable, and well‑documented data pipelines. High‑quality, trusted datasets that support critical business and healthcare decisions. Faster onboarding of new healthcare data sources and partners. Strong collaboration across engineering, analytics, product, and business teams. Continuous improvements in automation, monitoring, documentation, and engineering best practices. Why Join Us? Work on meaningful healthcare initiatives that improve patient outcomes. Gain hands‑on experience with modern cloud data architecture and healthcare interoperability standards. Collaborate with experienced professionals across engineering, analytics, product, and healthcare operations. Take ownership of impactful projects and grow your career in a rapidly evolving healthcare technology environment. If you’re excited about solving complex data challenges and building systems that make a real difference in healthcare, we’d love to hear from you. #J-18808-Ljbffr