Sift Healthcare is seeking a Senior Data Engineer to join our team.
Data is the backbone of what we do at Sift Healthcare. Our data engineers design and develop data pipelines to integrate disparate systems and curate data for machine learning. This role will leverage your strong understanding of data modeling principles and modern data platforms to develop intuitive data model architectures, extract-load-transform (ELT) processes, and testing infrastructure to ensure reliably robust data. Our engineers are not only motivated to research new solutions but to own the problem end-to-end.
We're looking for a candidate with 6+ years of experience working as a Data Engineer supporting ELT data pipelines and workflow orchestration tools. Experience with healthcare data will set you apart, as well as experience working in a startup environment.
JOB RESPONSIBILITIES
- Design, build, and implement generalized large-scale, sophisticated, and high-volume data pipelines for downstream analytics and data science.
- Perform continuous integration to ensure that every step of a data pipeline is testable and automated
- Lead technical design of scalable and flexible data architectures
- Re-architect existing code bases transitioning to new technologies and frameworks
- Document code, provide progress reports and perform code review and peer feedback
- Track milestones, activities and interdependencies across projects and tasks, with frequent status updates to stakeholders
- Continuously evaluate and identify improvements in the system processes and architecture
- Assist in maintaining data quality and fidelity in production systems
- Participate in Agile planning around data feature requests and advocate for the best data engineering projects in priority planning
- Mentor data engineering team members on coding, architecture, and data engineering processes
QUALIFICATIONS
- Minimum of a Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Economics or related field. Ideally, a Masters in a related field
- 6+ years of experience in a data engineering role
- 6+ years of programming experience, preferably in Python
- 6+ years of experience in Cloud data engineering in AWS stack, AWS certification is a plus
- 6+ years of experience in working with large data sets and pipelines (e.g., Hadoop, Spark, HBase)
- 6+ years of SQL experience, including performance tuning and query optimization
- Experience with healthcare data is a strong preference, specifically Epic, HL7, EDI, CDI
- Expertise in creating and maintaining production data pipelines using Airflow
- 3+ years of experience with schema design and data modeling
- Expert in code versioning and collaboration tools/repositories like GitHub
- Experience with container orchestration and deployment frameworks (e.g., Kubernetes, Docker) is preferred
- Experience in Cloud data engineering in AWS stack. AWS certification is a plus
- Strong debugging, critical thinking, and technical design skills with the ability to learn and apply new technologies quickly
- Excellent communication skills, supporting recommendations, design ideas, and analysis to team and stakeholders
- Experience in leading and mentoring other data engineers
COMPENSATION
Compensation will be based on skills and experience. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements).
ABOUT SIFT HEALTHCARE
Sift is a data science company working to improve payments processes in the healthcare industry. We are a growing and dynamic team that is serious about technology. Located in Milwaukee, Sift is thriving and looking for motivated team members who will help shape our culture. Sift offers competitive salaries and benefits. Learn more about Sift at www.sifthealthcare.com.
Job Type: Full-time
Pay: $110,000.00 - $190,000.00 per year
Benefits:
- Dental insurance
- Health insurance
- Health savings account
- Paid time off
- Vision insurance
Schedule:
Experience:
- Informatica: 1 year (Preferred)
- SQL: 3 years (Required)
- Python: 1 year (Preferred)
Work Location: Remote