Data Engineer III at Simplot utilizing advanced data engineering principles and cloud data tools. Collaborating in a team to support data solutions for food and agriculture industry.
About the role
- Business Intelligence Engineer at Welo Data designing and maintaining data infrastructure supporting analytics. Collaborating across teams to deliver high-quality, reliable insights from data.
Responsibilities
- Design, build, and maintain data pipelines and ELT/ETL workflows in AWS to support enterprise analytics and reporting.
- Develop and optimize dbt models that transform raw data into reliable, well-structured datasets for business use.
- Orchestrate workflows using Apache Airflow (MWAA) to ensure automation, reliability, and reproducibility of data processes.
- Partner with the Data Engineering team to align data architecture and ensure schema design supports analytics and business requirements.
- Monitor and optimize pipeline performance, reliability, and data quality across all layers of the data stack.
- Collaborate with analysts and business stakeholders to understand data needs and deliver governed, high-quality datasets.
- Build and maintain Power BI data models and support analysts in optimizing report performance and structure.
- Ensure data models and transformations are well-documented, version-controlled, and tested as part of a mature CI/CD analytics workflow.
- Engage with the broader analytics team to identify opportunities for automation, standardization, and improved data accessibility.
- Support Welo Data’s ongoing data quality and governance initiatives by ensuring accuracy, consistency, and traceability within pipelines and data models.
- Collaborate with the Data Quality & Governance Lead to identify and resolve data quality issues and contribute to continuous improvement of data management processes.
- Contribute to the development and maintenance of metadata, lineage, and documentation standards for analytics assets.
- Participate in sprint planning, retrospectives, and backlog grooming using Jira to manage tasks and progress.
- Document architecture decisions, data models, and workflows in Confluence to promote transparency and knowledge sharing.
- Operate effectively in an Agile environment, balancing technical rigor with responsiveness to evolving business needs.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, or a related field strongly preferred; equivalent experience acceptable.
- Minimum of 4 years of experience in data engineering, analytics engineering, or a related role with demonstrated impact in building and maintaining data pipelines and models.
- Proficiency in SQL and dbt for data transformation and modeling.
- Hands-on experience with AWS services, including Redshift, S3, Lambda, and Glue.
- Experience with Airflow (MWAA or similar orchestration tools) for workflow management.
- Familiarity with CI/CD workflows and version control using Git.
- Understanding of data warehousing concepts, dimensional modeling, and ELT design principles.
- Experience working within Agile methodologies, with practical use of Jira and Confluence for planning and documentation.
- Excellent communication and collaboration skills, with the ability to engage effectively across technical and non-technical stakeholders.
- (Preferred) Proficiency in Power BI, including data modeling and performance optimization.
- (Preferred) Knowledge of Python for automation and data pipeline development.
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
Job title
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