Senior Data Engineer - ETL & Integrations

Senior Data Engineer – ETL & Integrations About Lasso Informatics Lasso Informatics is a SaaS start-up with a live research data management and analysis platform that brings together multi-modal (imaging, genetics, behavioral, and biosample) data for large-scale studies. Thousands of researchers across the globe rely on our platform today, and we are rapidly iterating and improving to push the boundaries of what is possible in research data management. We live to innovate, and empower scientists to focus on the science, not the technology, leading to a faster time to science and cure. Our team is incredibly diverse both by background and expertise, and that is not by accident. We believe that the most creative and powerful solutions come from different ways of thinking about the world. You will be working in an inspiring ecosystem alongside world-renowned professionals in medicine, physics, engineering, imaging, epidemiology, software development, and genetics. We thrive on empowering our colleagues to be thought leaders and innovate fresh new solutions for an exciting and rapidly changing field. About the Role This is a senior-level data engineering and systems integration role focused on building and operating production-grade ETL pipelines and integrations. You will work across data ingestion, transformation, and loading while leveraging a BPMN-based workflow engine to model and manage process flows where appropriate. The role sits at the intersection of data engineering, backend development, and workflow-driven systems, with a clear distinction between ETL responsibilities and workflow orchestration capabilities. Key Responsibilities • Design, build, and operate end-to-end ETL pipelines and data integrations • Develop BPMN-based workflows to model and manage complex process flows • Build integration services and transformation logic in Java and Python • Integrate internal and external systems using REST APIs, API gateways, and asynchronous messaging • Apply appropriate data transformation and loading strategies (batch and near-real-time) • Design and optimize PostgreSQL schemas, queries, indexes, and bulk loading mechanisms • Work with structured and semi-structured data formats (JSON, CSV, XML, Parquet, Avro) • Ensure data quality, consistency, and reliability through validation, deduplication, and idempotency • Monitor, troubleshoot, and optimize production ETL pipelines and integration services • Collaborate with engineering, product, and external partners on integration contracts and data models • Document ETL pipelines, workflows, schemas, and operational procedures Required Skills & Experience • 5+ years of experience in data engineering, ETL, or systems integration roles • Strong experience building and operating production ETL pipelines • Proficiency in Python and/or Java in backend or data-processing environments • Strong PostgreSQL and SQL experience, including performance tuning • Hands-on experience with data transformation and loading techniques (ETL vs ELT, incremental loads, CDC concepts) • Experience integrating systems via REST APIs and API gateways • Experience working with BPMN-based workflow engines or workflow modeling tools • Experience operating distributed systems in production environments • Strong troubleshooting, debugging, and operational mindset • Familiarity with common architectural patterns (e.g., layered architectures, event-driven systems, integration patterns) Nice-to-Haves • Experience with specific BPMN workflow engines such as Camunda, Zeebe, or Flowable • Experience with event-driven architectures or message queues • Cloud platforms experience (AWS, GCP, or Azure) • Docker and Kubernetes experience • CI/CD pipelines for data or backend systems • Experience working in regulated or compliance-driven environments What Lasso Offers • Competitive salary and benefits package • In-office work culture with required presence Tuesday through Thursday • Opportunities for leadership and professional growth • Collaborative team committed to innovation, quality, and scientific impact • Access to training resources and ongoing professional development