About the Company
Headquartered in Birmingham, Alabama, Moultrie is a leader in game feeders and cellular camera innovation. The company develops products used by hunters, property owners, and others for real-time remote monitoring.
Moultrie is customer-driven, with hardware, software, marketing, and customer success teams working together to deliver a quality user experience. Its operating principles include customer obsession, excellence, bias for action, bold decision-making, delivering results, developing talent, continuous learning, and teamwork.
About the Role
Moultrie is seeking a Data Engineer to join its growing Data and Analytics (DnA) Team. The team develops data-driven insights that support business decision-making and is responsible for maintaining and expanding the foundational data layer in Snowflake.
In this role, you will build and maintain data pipelines, reconcile information from multiple source systems, and develop data models that support downstream applications and analytics. You will work with technologies including Fivetran, Azure Data Factory, APIs, web scraping, dbt, and Snowflake. The role also involves data quality, governance, documentation, and collaboration with stakeholders across marketing, operations, finance, and other business functions.
Working closely with the DnA Lead, data scientists, and technical teams, you will translate business questions into reliable data models and help align data products with departmental needs.
Key Responsibilities
Design, build, and maintain data pipelines that transfer information from source systems into Snowflake, including documented ingestion patterns and failure alerts.
Develop and maintain dbt data models across bronze, silver, gold, and platinum layers, supported by appropriate testing and documentation.
Build and maintain semantic models that make datasets suitable for natural language querying.
Evaluate downstream tools and contribute to selecting solutions that align with data architecture, project requirements, and business needs.
Translate business questions into reliable, repeatable data models, working with the DnA Lead to define requirements and prioritize delivery.
Collaborate with data scientists to develop models that support predictive modeling initiatives.
Implement and maintain data quality checks covering completeness, accuracy, testing, and appropriate thresholds.
Maintain naming conventions, attribute definitions, and contextual information that help business stakeholders understand and use data models.
Document incidents and root causes related to pipeline failures, data quality regressions, and other technical issues.
Track resolutions and identify incremental improvements to data pipelines and models.
Required Qualifications
At least four years of experience in data engineering or analytics engineering, including hands-on experience building and maintaining production-level data pipelines.
Strong SQL skills, including experience developing, maintaining, and optimizing modular logic in dbt.
Proficiency in Python for ingestion logic, data transformation, automation, and tasks such as web scraping.
Experience with Git and standard software development practices, including version control, code reviews, branching, and basic CI/CD.
Ability to translate ambiguous business problems into clear requirements and data models that support effective solutions.
Experience working through project sprints to deliver data solutions.
Strong documentation skills, including maintaining model definitions, data lineage documentation, and data dictionaries.
A collaborative working style and the ability to work effectively across data engineering, analytics, and business teams.
Preferred Qualifications
Experience in retail, consumer packaged goods (CPG), or consumer hardware.
Familiarity with streaming or event-driven data patterns.
Experience with Tableau, Streamlit, or similar tools that support collaboration with business analysts.
Exposure to machine learning workflows and feature store development to support data science initiatives.
Technology Stack
Extraction and ingestion: Fivetran, Azure Data Factory, APIs, and web scraping.
Transformation: dbt and Snowflake.
Loading and integration: APIs and cloud data ingestion.
Orchestration: Snowflake Tasks, Azure Data Factory jobs, and dbt jobs, with Airflow under evaluation.
Equal Opportunity / EEO
Moultrie is an equal opportunity employer and complies with applicable federal, state, and local fair employment practices laws. The company prohibits discrimination against employees, applicants, and other covered individuals based on race, color, sex, pregnancy status, age, national origin or ancestry, ethnicity, religion, creed, sexual orientation, gender identity, veteran status, disability, or any other protected class under applicable law.
This policy applies to all terms and conditions of employment, including hiring, training, promotion, discipline, compensation, benefits, and termination. Moultrie also complies with the Americans with Disabilities Act (ADA), as amended, and all applicable state and local laws.