Supervisor Data Engineering

Moda Health•Portland, OR

10h•$109,421 - $150,000•Remote

About The Position

Let’s do great things, together! About Moda Founded in Oregon in 1955, Moda is proud to be a company of real people committed to quality. Today, like then, we’re focused on building a better future for healthcare. That starts by offering outstanding coverage to our members, compassionate support to our community and comprehensive benefits to our employees. It keeps going by connecting with neighbors to create healthy spaces and places, together. Moda values diversity and inclusion in our workplace. We aim to demonstrate our commitment to diversity through all our business practices and invite applications from candidates that share our commitment to this diversity. Our diverse experiences and perspectives help us become a stronger organization. Let’s be better together. Position Summary The Data Engineering Supervisor leads a team of 5-7 engineers and architects while contributing directly to technical development. This role oversees enterprise data solutions, including data warehousing, ETL/ELT pipelines, and analytics engineering processes. The supervisor drives the implementation of scalable data transformation frameworks to support business intelligence and advanced analytics. They ensure data quality, governance, and performance optimization while guiding the team in building robust, automated solutions that enable data-driven decision-making across the organization. This is a FT WFH position. Pay Range $109,420.90 - $150,000.00 annually (depending on experience) This role may be classified as hourly (non-exempt) depending on the applicant's location. Actual pay is based on qualifications. Applicants who do not exceed the minimum qualifications will only be eligible for the low end of the pay range. Please fill out an application on our company page, linked below, to be considered for this position. https://j.brt.mv/jb.do?reqGK=27769232&refresh=true

Requirements

Proven leadership experience managing people and data-focused technical teams, with the ability to guide diverse, interdisciplinary teams with varying skill sets and experience levels.
7+ years of experience in data or analytics engineering with ETL/ELT pipeline design, development, and maintenance.
10+ years of SQL experience across on-prem servers (SQL Server) and cloud data warehouses (Snowflake, MS Fabric, BigQuery, Redshift).
Experience migrating on-prem databases to cloud data warehouses strongly preferred.
Expertise in data architecture principles, dimensional modeling, and enterprise data integration strategies.
Experience with data pipeline orchestration tools such as SSIS, SQL Agent, Tidal, Airflow, and dbt.
Ability to collaboratively develop and implement analytics and reporting solutions.
Strong understanding of data modeling principles, documentation, and tools.
Ability to communicate complex analytical solutions to audiences with varying technical understanding.
Strong organizational skills to plan, prioritize, and meet departmental goals and timelines.
Ability to work effectively under pressure in a complex, rapidly changing environment.
Ability to work independently with minimal supervision.

Nice To Haves

Healthcare data experience is preferred.
Experience supporting Power BI or other modern BI tools preferred.

Responsibilities

Oversee and coordinate data engineering and analytics engineering activities, including the design, development, implementation, and ongoing improvement and management of the Enterprise Data Warehouse (EDW).
Set clear objectives, monitor progress, and conduct regular performance reviews for the data engineering team.
Gather and translate business requirements into technical solutions by designing data models, building transformation workflows, and applying best practices for data architecture and governance.
Develop data models and pipelines while supervising the overall management of the EDW using diverse tools.
Collaborate with analytics and business teams, providing technical guidance, peer reviews, and support for ad hoc data queries and reporting needs.
Lead hiring, onboarding, training, coaching, and performance management to build a high-performing team.
Ensure compliance with data governance, security, and quality standards.
Continuously optimize processes to support data-driven decision-making.
Perform other duties as assigned.