Senior Data Engineer

Headquartered in Birmingham, Alabama, Moultrie ( is the leader in game feeders and cellular camera innovation, building products used by hunters, property owners, and others for real-time remote monitoring. We take pride in developing deep user understanding, obsessing about the details, and going the extra mile to show our users we love them. Moultrie is customer-driven – hardware, software, marketing, and customer success teams collaborate to deliver a quality user experience. We are guided by the following principles: Customer Obsession.; Excellence is the Standard.; Bias for Action.; Act Boldly.; Deliver Results.; Hire and Develop the Best.; Be Curious and Learn.; Win as a Team Job Summary Moultrie is looking for a Data Engineer to join the growing Data and Analytics Team. This team owns the development of insights from extraction that power decision-making across Moultrie. This role will contribute to maintaining and building upon the foundational data layer in Snowflake. The current engineering tech stack includes: Extraction/Ingestion: Fivetran, Azure Data Factory, APIs, Webscraping Transformation: dbt and Snowflake Loading/Integration: API, Cloud Data Ingestion Orchestration: Airflow is being evaluated, current stack is combination of Snowflake Tasks, ADF jobs, dbt jobs Typical engineering work includes ingesting and reconciling data across various source systems (such as telemetry logs, customer and subscription records, transactional data) and building logic in line with medallion architecture to produce models that can be integrated into downstream systems. Work will require strong data engineer fundamentals and the ability to engage cross-functionally with other business teams to align BI products with existing needs. The ideal candidate has expertise in full stack development and experience with stakeholder engagement and project-based development. This role works 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. Job Responsibilities Data Modelling and Pipeline Management Design, build, and maintain pipelines that move data from source systems into Snowflake with documented ingestion patterns and alert systems for failures. Model data at a bronze, silver, gold, and platinum level in dbt with appropriate tests and documentation. Build and maintain semantic models that translate datasets for natural language querying. Contribute to the evaluation and selection of which downstream tools align best with the data build based on project and business need. Translate business questions from other departments into reliable and repeatable data models, working with DnA Lead to scope requirements and inform sequencing. Work with the data scientist to build models that feed predictive modelling efforts. Data Quality and Governance Own data quality checks across the pipelines and models built including completeness, quality testing, and thresholds. Inform and maintain naming conventions, attribute definitions, and other context appropriate for analysis and utilization of data models for business stakeholders. Maintain incident and root cause documentation for pipeline failures, data quality regressions, and other bugs to ensure resolution and track incremental improvements. Job Requirements 4+ years in data engineering or analytics engineering with hands-on experience building and maintaining production level data pipelines. Strong SQL proficiency: Experience building and maintaining, and optimizing modular logic in dbt. Python experience: Proficiency with using python for ingestion logic, data transformation when necessary, and other automation processes such as webscraping. Experience with Git and standard software development practices: version control, code reviews, branching, and CI/CD basics. Ability to take an ambiguous business problem and work backwards to produce models that support effective solutions by creating a list of requirements and working through sprints to deliver. Strong documentation practices: able to produce and maintain model definitions, lineage documentation, and data dictionaries that enable other developers and business stakeholders. Collaborative working style: comfortable operating at the boundary between data engineering, analytics, and business teams. Preferred Qualifications Experience in retail, CPG, or consumer hardware. Familiarity with streaming or even-driven data patterns. This will become more important and the Data and Analytics function grows. Experience with Tableau, Streamlit, or other tools to facilitate development with business analysts. Exposure to machine learning workflows and feature store development to enable data science workflows. Essential Job Function We are an equal opportunity employer and comply with all applicable federal, state, and local fair employment practices laws. We strictly prohibit and do not tolerate discrimination against employees, applicants, or any other covered persons because of race, color, sex, pregnancy status, age, national origin or ancestry, ethnicity, religion, creed, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, training, promotion, discipline, compensation, benefits, and termination of employment. We comply with the Americans with Disabilities Act (ADA), as amended by the ADA Amendments Act, and all applicable state or local law. #J-18808-Ljbffr EBSCO Industries, Inc.