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365 Retail Markets is the most trusted global provider of unattended retail technology, delivering conveniently smart self-service solutions since 2008. The company’s all-in-one platform powers retail spaces across food service, global retail, and hospitality with a comprehensive suite of frictionless smart stores, micro markets, vending, catering, and dining point-of-sale options. These technologies can be found worldwide in corporate offices, manufacturing and distribution facilities, educational campuses, hotels, and beyond.As a nine-time honoree on the Inc.
5000 list of fastest-growing companies in the United States, and with a continually expanding global presence, 365 Retail Markets is committed to growth, innovation, and providing superior, integrated technology that meets the evolving needs of its customers and consumers. We are seeking a skilled Senior Data Engineer to join our lean, agile team dedicated to building a robust data infrastructure. This role will be instrumental in developing our foundational data warehouse and implementing best practices to support our data strategy roadmap.
Reporting to the Software Engineering Leader, you will collaborate closely with the Senior Data Product Manager and product leadership to ensure alignment on data initiatives and deliver high-impact solutions.
Responsibilities
- Data Pipeline Development: Design, build, and maintain scalable data pipelines using ETL processes to ensure seamless data flow from various internal and external sources (e.g., SQL databases, APIs) to our data warehouse.
- Data Integration and Warehousing: Implement and manage data warehousing solutions (e.g., Snowflake, Redshift) to support analytics and reporting needs, ensuring data accuracy and consistency.
- Operational Efficiency: Optimize data workflows for performance and reliability, focusing on practical implementations that meet immediate and long-term business needs.
- Cross-Functional Collaboration: Work closely with cross-functional teams, including data analysts and product managers, to gather requirements and deliver data solutions that support analytics and reporting.
- Data Quality Assurance: Monitor data quality and integrity throughout the data lifecycle, implementing standards and processes to ensure reliable data for analysis.
- Documentation: Create and maintain documentation for data workflows, data models, and engineering best practices to facilitate knowledge sharing and team collaboration.
- Agile Practices: Participate in Agile methodologies to support the iterative development of data solutions, ensuring timely delivery of project milestones.
- Support Ad-Hoc Requests: Respond to ad-hoc data requests from stakeholders, providing timely and accurate data to inform business decisions.
Requirements
- 5-7 years experience in data engineering with data warehousing/data lakes.
- SQL Expertise: Proficient in writing complex SQL queries for data retrieval and manipulation.
- ETL Experience: Strong background in designing and implementing ETL processes and data integration workflows.
- Data Warehousing Knowledge: Familiarity with data warehousing technologies (e.g., Snowflake, Redshift) and data modeling techniques.
- Programming Proficiency: Experience in programming languages such as Python or Java for data manipulation and pipeline development.
- Data Pipeline Orchestration: Familiarity with orchestration tools (e.g., Apache Airflow, Fivetran) for automating data workflows.
- Cloud Platform Experience: Knowledge of AWS services, including S3 for data storage and retrieval.
- Data Quality Assurance: Ability to monitor data quality and implement standards for data integrity.
- Version Control: Familiarity with version control systems (e.g., Git) for managing code changes.
- Problem-Solving Skills: Strong analytical skills for troubleshooting and optimizing data processes.
- Collaboration Skills: Excellent communication abilities to work effectively with technical and non-technical stakeholders.
Preferred Skills
- Experience with cloud platforms (AWS, GCP) for deploying and managing data solutions.
- Familiarity with data visualization tools (e.g., Power BI, Tableau) and their integration with data pipelines.
- Understanding of data governance principles, data security, and compliance standards relevant to data management.
- Previous experience in Consumer-Packaged Goods (CPG) or a related industry is a plus.
