Sr Analytics Engineer

Colonial Pipeline Company•Atlanta, GA

12d•Onsite

About The Position

The Senior Analytics Engineer plays a vital role on the Data Team, designing, developing, and implementing comprehensive data and analytics solutions for stakeholders across Colonial Pipeline Company. Working closely with cross-functional teams, this role helps provide accurate and efficient access to data so teams can make informed decisions, identify opportunities, and solve business problems. The position follows a typical weekday schedule and is based in Alpharetta, Georgia, with travel up to 10% of the time.

Requirements

Bachelor’s degree in a related field or equivalent experience.
Five or more years of experience in data modeling, data engineering, analytics, analytics engineering, or a related area.
Advanced SQL and Python skills.
Strong experience with data modeling, data engineering principles, and software engineering best practices.
Experience with CI/CD practices and developing reliable, maintainable code.
Strong data visualization and storytelling skills.
Experience with Power BI, Power Apps, or a similar platform.
Experience with data validation, automated workflows, testing, and orchestration.
Experience with ETL tools such as Alteryx or Azure Data Factory.
Experience working with data from multiple platforms, including Oracle, SSIS, Azure, and APIs.
Strong written and verbal communication skills, including the ability to clearly explain complex business activities, technical requirements, and recommendations.
A solutions-oriented mindset and the ability to collaborate effectively with leaders, employees, contractors, consultants, and vendors.

Nice To Haves

Experience with machine learning and advanced analytics.
Knowledge of DevSecOps practices.
Cloud platform experience.
Experience with dbt, including testing and workflow orchestration.
Experience with real-time data solutions.

Responsibilities

Identify and resolve efficiency blockers so that the Data Program can iterate faster.
Build, deploy, and maintain data models and ETL pipelines for analytics, data science, and other business use cases.
Develop and maintain analytics products that drive measurable business outcomes.
Partners with functional teams to identify opportunities, solve business problems, and translate stakeholder needs into technical metrics and documentation.
Advise business groups on the effective use of data.
Collaborate with Data Governance to define data quality rules, standards, and metrics.
Establish software engineering best practices for code used in analytics data products.
Develop business intelligence solutions and data visualizations that support business functions.
Partner with Data Science to develop AI, machine learning, and advanced analytics solutions.
Work with the Data Platform team to define enterprise data pipeline and data curation needs.
Embed a DataOps philosophy into day-to-day work.
Support the company’s emergency response efforts when needed, including training, short-term travel, and backfill duties.