Staff Data Engineer

The Staff Data Engineer will support our software developers, database architects, analysts, and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. At IMO, our data is not merely a side effect or bonus; it is the core of our products, the mission critical deliverable for our clients. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.

Join our growing Product Development/Terminology Data Engineering Organization as a Staff Data Engineer to help design, create, and support high quality solutions that support 80% of US clinicians and build the application of Data Engineering within IMO!

• Leverage IMO’s terminology data to inform work, ensuring awareness of its critical role in IMO products.
• Analyze, enhance, and develop IMO products by directly interacting with code, data, and infrastructure.
• Work with large, complex data sets, applying technical skills and deep knowledge of terminology data to drive insights and improvements.
• Design, build, and optimize data infrastructure for ETL processes using SQL, AWS, and big data technologies, ensuring scalability, reliability, and efficiency.
• Automate and improve data workflows, reducing manual processes, optimizing performance, implementing orchestration frameworks, and enhancing data pipeline infrastructure.
• Develop and maintain data platform components for bulk, transactional, and streaming access, ensuring system scalability and cost-efficiency.
• Ensure data quality and integrity by maintaining schemas, improving data models, executing data management procedures, and promoting best practices.
• Develop and document quality source code
• Contribute to Agile development, fostering collaboration, accountability, and continuous improvement through testing, transparency, and adaptability.
• Provide mentorship and leadership, offering feedback and guiding colleagues to improve team capabilities.
• Deliver quality outputs through testing, transparency, inspection, and adaptation
• Take ownership and proactively anticipate impacts, implementing creative solutions to technical challenges and embracing innovative thinking.
• Collaborate cross-functionally with stakeholders to translate business needs into technical solutions, assist with data/infrastructure, and drive product innovation.
• Stay ahead of industry best practices, continuously developing skills and making data-driven decisions that guide the team.

• Relevant Technical BA/BS degree + 7 years of experience OR 10+ years of relevant professional experience.

• Experienced engineer with a track record of building end-to-end data platforms, collaborating on architecture, and leading peers.
• Proficient developer in multiple languages, including Python, with the ability to quickly learn new ones.
• Expertise in SQL (complex queries, relational databases like PostgreSQL, and NoSQL databases like DynamoDB, MongoDB, Elasticsearch).
• Extensive big data experience, including Spark, Kafka, and optimizing data pipelines, architectures, and datasets.
• Strong background in data modeling, logical/physical database design, and metadata management.

• AWS expert with hands-on experience in EC2, EMR, RDS.
• Proficient in CI/CD development using Git, Terraform, and agile methodologies.
• Comfortable with stream-processing systems (Storm, Spark-Streaming) and workflow management tools (Azkaban, Luigi, Airflow).

• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to guide teams through root cause analysis and process improvements.
• Experienced mentor and cross-departmental leader with strong communication skills.
• Enjoys challenges, explores new approaches, and is comfortable asking for help.

• Hands-on experience leveraging AI technologies to enhance efficiency and effectiveness.
• Exposure to knowledge graph technologies (Graph DB, OWL, SPARQL) is a plus.

• AWS Associate: Data Engineer, Solutions Architect (at least one strongly preferred)
• AWS Associate: Machine Learning Engineer (preferred, not required)
• AWS Foundational: AI Practitioner (preferred, not required)

• Hands-on with ETL & BI tools (Talend, Tableau, Looker).
• Deep understanding of data cataloging standards and their maintenance.
• Prior experience working with healthcare data.