Senior Data Engineer

Senior Data Engineer

Optomi, in partnership with a leading distributor of wine and spirits, is seeking a Senior Data Engineer for their Atlanta, GA location.

Candidates must be able to combine raw information from different sources to create consistent and machine-readable datasets that are easy to analyze and support company initiatives.

They will support other Data Engineers and Data Analysts on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.

They will also implement methods to improve data reliability and quality, improve data visibility and reduce effort through automation.

This Data Engineer will enjoy working for a company on the Forbes 2023 list of America's Best Large Employers!

What the right candidate will enjoy!

• Working for one of the nation's leading wholesale beverage alcohol distributors!
• The ability to work 2 days remotely!
• 401k with company matching!
• Medical, dental, and vision benefits!
• Generous paid time off program!

Experience of the right candidate :

• Bachelor's / Tech School degree in Computer Science, Information Systems, Engineering or equivalent and / or commensurate years of real-world experience in software engineering.
• 4+ years of relevant experience in data management.
• 3+ years in data engineering with detailed knowledge of data warehouse technical architectures, infrastructure components, ETL / ELT.
• Experience with performance analysis and optimization.
• Experience in data acquisition, transformation and storage design using design principles, patterns and best practices.
• Strong hands on experience with Snowflake, Python, and cloud technologies.

Responsibilities of the right candidate :

• Contribute on a team of data engineers through design, demand delivery, code reviews, release management, implementation, presentations, and meetings.
• Mentor fellow data engineers and contribute to ongoing process improvements for the team.
• Evaluate business needs and objectives and align architecture / designs with business requirements.
• Build the data pipelines required for the optimal extraction, transformation, integration and loading of raw data from a wide variety of data sources.
• Assemble large, complex data sets and model our data in a way that meets functional / non-functional business requirements.
• Create data tools for analytics team members that assist them in generating innovative industry insights that provide our business a competitive advantage.
• Implement data tagging mechanisms and metadata management so data is accurately classified and visible to the organization.
• Build processes to help identify and improve data quality, consistency and effectiveness.
• Ensure our data is managed in a way that it conforms to all information privacy and protection policies.
• Use agile software development processes to iteratively make improvements to our data management systems.
15 days ago