About the Role:

As a Senior Data Engineer in Mendel’s customer delivery team, you will help architect and implement solutions allowing our customers to fully realize value from the Mendel AI platform. You will serve as a primary technical point of contact to the customer, working with them during post-sales implementation to ensure we support their end to end clinical data analytical needs powered by Mendel's AI capabilities.

To be successful in this role, you must balance technical data engineering expertise with exceptional communication skills with technical and non technical stakeholders to ensure successful project execution and customer satisfaction.

You Will:

• Navigate and assess customer's complex data infrastructure landscape across various cloud environments including AWS, Azure and GCP to build a deployment solution design.
• Design, develop and support data pipelines and workflows that integrate various sources of structured and unstructured medical data across our customers' landscape with the Mendel AI platform.
• Assess and implement any customizations and custom data wrangling needed to transform customer datasets in a way that is best suited for processing by our ML models.
• Monitor data processing and machine learning workflows to ensure customer data is successfully processed by our ML models, debugging and resolving any issues faced along the way.
• Generate necessary data artifacts and analytics needed to assess the quality of results generated by different parts of the AI workflow to ensure they meet desired quality standards.
• Collaborate closely with the AI team to assess model performance and improve results as needed.
• Collaborate closely with Product Engineering as needed to resolve any issues faced during customer deployment and onboarding.
• Collaborate closely with Customer Success Managers and Account managers to maintain close customer relationships and ensure customer satisfaction.
• Develop tooling and playbooks to streamline and automate key technical delivery activities to be repeatable and scalable.

You Have:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field with 6+ years of data engineering experience.
• ETL or Pipeline design/implementation with Large Datasets.
• Experience with distributed processing systems like Spark, Kubernetes, Elasticsearch, and familiarity with operational visibility tools like Prometheus, Loki and Grafana.
• Fluency required with SQL and Python with bonus points for also being proficient in Java.
• Experience in AWS and GCP cloud environments.
• Prior customer facing experience with demonstrable ability to communicate effectively with both technical and non-technical stakeholders and partners at all levels.
• Experience building relationships with and collaborating cross functionally across Product, Engineering and AI teams to achieve customer outcomes.

Nice to Have:

• Healthcare domain experience handling EHR and Claims data will be a huge plus.
• Recent experience building data pipelines supporting Machine Learning workflows.

Compensation

• $170,000.00 - $200,000.00

Message to applicants applying to work in the U.S.:
When available, the salary range posted for this position reflects the projected hiring range for new hire salaries in U.S. locations. For non-sales roles, the hiring ranges reflect base salary and do not include bonuses, equity, or benefits. Hiring ranges for sales positions include base and incentive target, and do not include equity or benefits. Individual pay is determined by the candidate’s hiring location and additional factors, including but not limited to skillset, experience, and relevant education, certifications or training. Applicants may not be eligible for the full salary range based on their U.S. hiring location. The recruiter can share more details about compensation for the role in your location during the hiring process.