Data Engineer III

About Transcarent
Transcarent and Accolade have come together to create the One Place for Health and Care, the leading personalized health and care experience that delivers unmatched choice, quality, and outcomes. Transcarent’s AI-powered WayFinding, comprehensive Care Experiences – Cancer Care, Surgery Care, Weight – and Pharmacy Benefits offerings combined with Accolade’s health advocacy, expert medical opinion, and primary care, allows us to meet people wherever they are on their health and care journey. Together, more than 20 million people have access to the combined company’s offerings. Employers, health plans, and leading point solutions rely on us to provide trusted information, increase access, and deliver care

Base salary range is $135,000-$145,000

This is a hybrid role working from our Seattle, WA office 2-3 days per week.

We are unable to provide H1B Sponsorship at this time.

Role overview

As a Data Engineer III at Accolade, you will be a key technical leader on our enterprise data platform team, architecting, designing, and implementing cutting-edge cloud-native, service-oriented data solutions with minimal oversight. You will take full ownership of complex data engineering initiatives, drive architectural decisions, and mentor junior team members while delivering mission-critical analytics capabilities that support the company's strategic objectives. Leveraging your deep expertise in AWS technologies, Databricks, and advanced data engineering principles, you will independently transform complex business challenges into scalable, high-performance data solutions that drive strategic insights across the organization.

A day in the life…

• Architect, develop, and maintain enterprise-scale data pipelines that process massive volumes of healthcare data with exceptional reliability and performance Design and evolve our Enterprise Data Warehouse structure, establishing advanced optimization strategies for query performance and data accessibility

• Drive the implementation of complex data integration solutions that connect diverse systems including Telephony, CRM, and various internal applicationsDevelop sophisticated data processing frameworks using Python, PySpark, and other advanced data engineering tools

• Implement and optimize complex Databricks notebooks and jobs for large-scale data transformationBuild and optimize advanced data models in AWS environments including RedShift, RDS, DynamoDB, and S3Design and implement comprehensive Databricks workflows for data processing, utilizing Delta Lake architecture and highly optimized Spark jobs.

• Collaborate with executive stakeholders and cross-functional teams to translate complex business requirements into innovative data solutionsImplement and enforce advanced data quality control mechanisms to ensure data integrity throughout the data lifecycle.

• Participate in sprint planning and provide technical leadership for complex data engineering initiatives.

• Research and evaluate emerging technologies, making recommendations for technology adoption and platform evolution

• Lead and mentor development team members while driving technical excellence across data engineering initiatives.

What we are looking for…

In addition to being able to carry out the above responsibilities, we're looking for someone comfortable working independently in a fast paced, ever changing environment who has extensive experience with enterprise data transformation/warehousing, as indicated by the following attributes:

• 5+ years of professional data engineering experience with demonstrated progression in technical leadership roles.

• BS or MS in Computer Science, Data Science, or related field.

• Expert-level proficiency in Python with extensive experience building enterprise-scale data processing applications.

• Advanced expertise with Databricks platform, including Delta Lake, Spark SQL, and Databricks workflows.

• Proven track record of designing and implementing large-scale data warehousing solutions and complex ETL/ELT pipelines.

• Expert-level knowledge of SQL with experience in advanced query optimization and performance tuning.

• Deep expertise with AWS data services, particularly RedShift, S3, Glue, Lambda, RDS, and DynamoDB.

• Extensive experience with modern data processing frameworks such as Apache Spark, Airflow, or similar tools.

• Strong expertise in data modeling concepts and best practices for dimensional modeling.

• Advanced understanding of performance tuning and optimization techniques for data systems.<