Senior Data Engineer

Collective Health•Plano, TX

1d•$132,000 - $165,000•Hybrid

About The Position

At Collective Health, we’re transforming how employers and their people engage with their health benefits by seamlessly integrating cutting-edge technology, compassionate service, and world-class user experience design. We deliver a connected healthcare experience for over a quarter million members and 60+ companies across the nation who want the best for their employees. We've got a ton of interesting problems to solve around data pipeline design and implementation, data architecture and modeling, distributed systems, and more. If you're passionate about tackling hard problems while making a real difference in the world, we'd love to talk!

Requirements

BS degree in Computer Science or related technical field, or equivalent practical experience
4+ years proven work experience as a data engineer, working with at least one programming language (e.g. Scala, Python/PySpark) plus SQL expertise
4+ years experience with schema design, dimensional data modeling, and large-scale data warehousing architecture
Expertise in building data pipelines through efficient ETL design, implementation and maintenance
Background working with distributed data systems such as Spark, Presto, Hive, and Redshift.
Excellent communication skills to collaborate with stakeholders in Engineering, Product, Data Science, Analytics/BI, and Operations

Nice To Haves

Experience with BI platform administration and/or schedulers/workflow management tools (e.g. Airflow) a plus

Responsibilities

Data Infrastructure Orchestration - Build and maintain cloud native infrastructure for Data Platform (AWS, Terraform)
Data Pipelines - Create new pipelines and improve/maintain existing pipelines using Spark (Python, Pyspark, SQL)
Data Modeling - Partner with analytic consumers to design logical and physical schemas, improve existing data models and build new ones
Cross-functional Collaboration - Interface with Product, Engineering, Data Science, Analytics/BI, and Operations to understand their data needs, providing both consultative and data engineering solutions for consumers
Build data expertise and own data quality across various business domains including healthcare claims and member experience
Manage the Business Intelligence development lifecycle, from semantic model development and version control to user administration, ensuring high data quality and consistency from the pipeline through to the visualization layer.
Enable fellow developers to “self-service” their data needs
Leverage best in industry practices to build the next generation data ecosystem to collect, move, store and analyze data