Data Analytics Manager | Lead Insights & Governance

Schweitzer Engineering Laboratories, Inc.; Pullman (WA); On-site; USD 136,000 - 147,000; Full time

Benefits offered by this job

Competitive pay

Superior benefits

Employee-owned company

ESOP

Job summary

Schweitzer Engineering Laboratories (SEL) seeks a Data Analytics Manager to transform data into actionable insights that improve products, processes, and outcomes. You will lead a team of Data Analysts delivering trusted data and scalable analytics across Manufacturing, Engineering, Quality, and Information Services.

You will advance analytics capabilities through governance, self-service reporting, and data-informed decision-making, collaborating with Data Engineers and Data Scientists to build

Qualifications

• Bachelor's degree in Math, Statistics, Data Science, or related technical discipline.

Responsibilities

• Lead, mentor, and develop a team of Data Analysts, fostering technical excellence and customer-focused mindset.
• Oversee analytics projects and reporting initiatives with high-quality deliverables.
• Partner with business leaders to identify data-driven improvements and analytics solutions.
• Build alignment across cross-functional teams to advance analytics initiatives and data governance.
• Establish processes ensuring data integrity, traceability, and trust across reporting and analytics.

Skills

SQL

Python

R

Leadership

Data governance

Power BI

Microsoft Fabric

Data analysis

Stakeholder management

Education

Bachelor's degree in Math/Statistics/Data Science

Master's degree in Math/Statistics/Data Science

Tools

Power BI

Microsoft Fabric

Azure

Job description

Schweitzer Engineering Laboratories (SEL) seeks a Data Analytics Manager to transform data into actionable insights that improve products, processes, and outcomes. You will lead a team of Data Analysts delivering trusted data and scalable analytics across Manufacturing, Engineering, Quality, and Information Services.

You will advance analytics capabilities through governance, self-service reporting, and data-informed decision-making, collaborating with Data Engineers and Data Scientists to build