Senior Data Engineer & Analytics Leader

Pratt & Whitney; Springdale (AR); On-site; USD 108,000 - 205,000; Full time

Job summary

Pratt & Whitney is seeking a data engineering professional to design and maintain scalable data pipelines and curated datasets that support analytics, reporting, and informed decision-making.

You will integrate data from enterprise apps, spreadsheets, databases, and APIs, develop BI visuals, and ensure data quality and governance across enterprise data assets. Collaboration with IT, operations, and customers is essential to translate requirements into practical analytics solutions.

Qualifications

• Advanced degree with 5+ years in IT Infra, data analytics, or related tech.
• Bachelor’s with 8+ years, or Associate with 10+ years.
• High School/military with 12+ years of experience.
• 5+ years in data engineering, analytics, BI, or related tech.
• Experience with Power BI and SQL.
• Experience in data quality, governance, warehousing, modeling.

Responsibilities

• Design, build, and maintain reliable data pipelines and datasets for analytics.
• Integrate and standardize data from diverse sources including apps, spreadsheets, databases, and APIs.
• Develop data visualizations, statistical analyses, and reporting solutions.
• Improve data quality, governance, and documentation for trusted data.
• Collaborate with customers to translate requirements into data/analytic solutions.
• Lead projects using appropriate software development and Agile practices.

Skills

Power BI

SQL

Data engineering

Data analytics

Agile

Data modeling

Education

Advanced degree & 5+ yrs in IT/Analytics

Bachelor’s with 8+ yrs

Associate with 10+ yrs

High School/Military +12 yrs

Tools

Azure

Databricks

Snowflake

Delta Lake

Power Automate

Power Apps

Git/CI/CD

Job description

Pratt & Whitney is seeking a data engineering professional to design and maintain scalable data pipelines and curated datasets that support analytics, reporting, and informed decision-making.

You will integrate data from enterprise apps, spreadsheets, databases, and APIs, develop BI visuals, and ensure data quality and governance across enterprise data assets. Collaboration with IT, operations, and customers is essential to translate requirements into practical analytics solutions.