Data Engineer (Remote)

Talon Hiring Solutions has a client that is looking for a Data Engineer to join the Data and Analytics Team. This team owns the development of insights from extraction that power decision-making. The role will contribute to maintaining and building upon the foundational data layer in Snowflake.  The current engineering tech stack includes; Fivetran, Azure data Factory, APIs, Webscraping, dbt, Snowflake,APO, and Cloud Data Ingestion.  The ideal candidate has expertise in full stack development and experience with stakeholder engagement and project -based development.  This role will work closely with the DnA Lead, internal stakeholders across the business, and technical teams in marketing, operations, and finance that own department specific tools that depend on data for activation.

Our client is a customer-driven company that values innovation, collaboration, curiosity, and delivering results. The team works together to build products and experiences that make a meaningful difference for customers.

*This role is fully remote with some travel to the home office in Birmingham, AL*

What You'll Do

• Build, maintain, and optimize data pipelines that ingest information from multiple source systems into Snowflake.
• Develop and maintain scalable data models using dbt, following bronze, silver, gold, and platinum modeling practices.
• Create reliable data solutions that support reporting, business intelligence, analytics, and downstream applications.
• Use SQL and Python to transform data, automate processes, build ingestion logic, and support integrations such as APIs and web scraping.
• Partner with business teams across Marketing, Operations, Finance, and other departments to understand data needs and translate business questions into practical data solutions.
• Establish and maintain data quality checks, testing, documentation, naming conventions, and data definitions.
• Monitor pipelines, troubleshoot failures, and document root causes and solutions to continually improve data reliability.
• Build semantic models that make data easier to understand and use, including supporting natural-language querying.
• Collaborate with the Data & Analytics Lead and Data Scientist to develop datasets that support predictive analytics and machine learning initiatives.
• Participate in project planning, requirements gathering, sprint development, code reviews, and other software development practices.
• Help evaluate and implement data tools and technologies as Moultrie's data and analytics capabilities continue to grow.

What You'll Bring

• 4 years of experience in data engineering, analytics engineering, or a similar role building and supporting production data pipelines.
• Strong SQL skills with experience developing modular, scalable, and optimized logic in dbt.
• Proficiency in Python for data ingestion, transformation, automation, web scraping, and other engineering applications.
• Hands-on experience with Snowflake and modern data engineering practices.
• Experience with data integration and ingestion tools such as Fivetran, Azure Data Factory, APIs, or web scraping.
• Familiarity with Git, version control, branching, code reviews, and CI/CD practices.
• Strong understanding of data modeling, data quality, testing, and documentation.
• Ability to take an ambiguous business need, identify requirements, and develop a practical data solution from concept through delivery.
• Strong communication and collaboration skills with the ability to work effectively with both technical and non-technical stakeholders.
• A proactive, problem-solving mindset and the ability to work independently while collaborating closely with a growing Data & Analytics team.
• Experience in retail, CPG, consumer products, or consumer hardware.
• Exposure to streaming or event-driven data.
• Experience with Tableau, Streamlit, or similar analytics and visualization tools.
• Familiarity with machine learning workflows, predictive modeling, or feature stores.
• Experience working with modern data architectures such as medallion architecture.