Senior Data Engineer

Description

At Commence, we’re the start of a new age of data-centric transformation, elevating health outcomes and powering better, more efficient process to program and patient health. We combine quality data-driven solutions that fuel answers, technology that advances performance, and clinical expertise that builds trust to create a more efficient path to quality care.

With human-centered, healthcare-relevant, and value-based solutions, we create new possibilities with data. We provide proof beyond the concept and performance beyond the scope with a focus on efficiencies that transform the lives of those we serve. With a culture driven by purpose, straightforward communication and clinical domain expertise, Commence cuts straight to better care.

As a Sr. Data Engineer you will be responsible for designing, building, and maintaining efficient, scalable, and fully automated data pipelines and architectures that support various business needs ranging from operational reporting to sophisticated AI/ML analytics. The ideal candidate will have a strong background in data engineering, cloud technologies, and data management practices at scale using modern data platforms and tools.

• Design, develop, and maintain scalable data pipelines to collect, process, and transform data from various sources.
• Integrate data from multiple sources, ensuring data quality and consistency across the organization.
• Build and maintain data storage solutions, including data warehouses and data lakes, ensuring optimal performance and reliability.
• Implement data transformation and enrichment processes to prepare data for analytics and reporting.
• Leverage cloud technologies, particularly AWS, to optimize and manage data infrastructure.
• Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions.
• Create and maintain comprehensive documentation for data pipelines, data models, and related processes.
• Mentors and guides junior data engineers/ analysts on data engineering best practices and industry standards.
• Other duties as assigned.

• Minimum of 4 years of experience in data engineering or a related field.
• Strong experience with data pipeline/orchestration and ETL development using tools such as Apache Airflow, Kubernetes, Databricks Workflows or similar.
• Demonstrated experience in designing highly efficient programs capable of processing terabytes of data.
• Strong Proficiency in SQL and experience with relational databases (e.g., SQLServer, Postgre
  
  SQL) and No
  
  SQL databases (e.g., Mongo
  
  DB, Open Search).
• Experience with cloud technologies, particularly AWS (e.g., S3, Redshift, Glue, Lambda, Athena).
• Proficient in writing data programs in R, Python, Scala, or similar language.
• Familiarity with big data technologies such as Apache Spark, Databricks, or similar.
• Familiarity with data visualization tools and data migration methods.
• Excellent problem-solving skills and attention to detail.
• Strong communication and interpersonal skills, with the ability to work effectively with diverse teams and stakeholders.

• Bachelor’s degree in computer science, Information Technology, or a related field.

• Familiarity with data governance and data quality best practices is a plus.
• Familiarity with healthcare data standards i.e. (FHIR, HL7)
• Familiarity working with unstructured data i.e. pdfs, free-text, etc.
• Databricks Data Engineering certifications.
• Data Visualization/ Reporting skills (i.e. Power
  
  BI, Tableau, or Quicksight)

Commence.

AI is committed to providing equal employment opportunities to all applicants, including individuals with disabilities. If you require a reasonable accommodation to participate in the application process due to a disability, please contact Human Resources at  or hr.
Please note that unless you are requesting accommodation, all applications must be submitted through our online application system.