Data Engineer

• Develop, test, and deploy ETL pipelines across multiple data sources within an established ingestion framework
• Build integrations with third-party tools, APIs, and services to ensure data is synchronized and accessible
• Monitor data pipelines, troubleshoot failures, and resolve issues with guidance from a senior engineer
• Build and maintain approximately 10 BI dashboards supporting 2-3 partner teams
• Ensure dashboard accuracy, performance, usability, and retirement of outdated or unused reports
• Write and maintain data tests, including source-level data quality checks
• Contribute to data modeling and transformation logic in dbt
• Respond to one-off business questions through a managed intake queue
• Maintain clear documentation for pipelines, workflows, and dashboards
• Participate actively in code reviews as both an author and reviewer

Skill Breakdown

• 60% Data pipeline / ETL engineering
• 25% BI dashboard development and maintenance
• Remaining focus on documentation, ad hoc requests, testing, and collaboration

Database Extract Transform and Load (ETL), Test Plan/Schedule, Application Programming Interface (API), Problem Solving Skills, Identify Issues, Data Management, Reporting Dashboards, Business Intelligence, Usability Engineering, Data Quality, * 1-3 years of experience in data engineering, analytics engineering, or a closely related data-focused role

• Strong SQL skills for querying, transforming, and validating data
• Working knowledge of Python for data engineering tasks
• Experience with BI tools such as Power BI, Tableau, Looker, Sigma, or similar
• Familiarity with cloud data warehouses such as Snowflake or Redshift
• Exposure to dbt or strong willingness to learn
• Familiarity with Git/version control
• Comfortable asking questions and interested in understanding business context behind the data

Preferred Qualifications

• Experience with Snowflake Cortex
• Exposure to low-code ETL/ingestion tools such as Fivetran
• Experience with transformation frameworks such as dbt
• Exposure to orchestration tools like Airflow
• Familiarity with AWS services such as S3, Lambda, or SQS
• Experience building API integrations
• Data modeling experience through work, internship, or coursework
• Industry experience is a plus, We’re looking for someone who is technically solid in SQL and Python, excited to deepen their experience in data engineering, and motivated by mentorship and growth. This person should be comfortable owning dashboard work in addition to pipeline development and should value collaboration, curiosity, and team fit.