Seasonal Data Engineer

See’s Candies•San Francisco, CA

9h•$65 - $75

About The Position

Work is Sweet! 'Quality without Compromise' is not just a motto at See’s Candies. It is the most important ingredient in our recipe for success. See’s Candies has been in business since 1921 and maintains a reputation for producing the highest quality candy and providing superior customer service. See’s is a leader in the confectionery industry with over 250 retail shops across the USA, a growing e-commerce business, and expanding opportunities internationally. We are seeking friendly, enthusiastic individuals who are passionate about helping us grow and thrive in our second century. Job Description Summary: POSITION OBJECTIVE: The Data Engineering - Data & Analytics (Contractor) will support the enterprise analytics platform by building, maintaining, and enhancing data pipelines and data lake infrastructure within Azure. Embedded within the Data & Analytics team, this role works closely with analysts to ensure timely, accurate, and reliable data availability for reporting and analytics needs. The position is execution-focused, providing backend engineering support for data ingestion, transformation, testing, and platform stability, while working independently within established priorities to maintain continuity, performance, and data integrity across the analytics environment. The pay range for this position at commencement of employment is expected to be between $65-$75 per hour; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Job Description:

Requirements

Bachelor’s degree or higher in Computer Science, Engineering, Technology or related field; equivalent related work experience may be considered in lieu of degree.
Solid knowledge of Azure analytics components such as Azure Data Lake Storage, Azure Data Factory, Databricks, Azure SQL, Synapse / SQL Data Warehouse, Azure Analysis Services, Azure ML and Power BI Services required.
Experience developing Power BI data models and reports.
4+ years’ experience in business data warehouse and analytics / BI architectures, including design and development across multiple technologies and analytical platforms.
2+ years’ experience in analytical development leveraging Azure analytics components end-to-end.
Experience supporting data pipelines, data preparation, or analytical workflows used for machine learning or AI-driven analytics initiatives.
Experience delivering analytics development, including backlog planning, building, testing, and delivery.
Proven ability to learn new technologies quickly and manage change efficiently, proactively, and in a positive manner.

Nice To Haves

Experience working in a retail and/or manufacturing organization; food and beverage experience a plus.

Responsibilities

Build and manage Data Lake ingestion and staging of data from various disparate sources for analytics and storage purposes using Azure Data Factory.
Design and implement Data Lake lifecycle processes that support effective data provisioning capabilities to support enterprise project requirements.
Implement and manage ELT routines using Azure Data Factory to extract, load, and transform data into Azure SQL Data Warehouse.
Provide Databricks and ML platform support, assisting analysts with data preparation and pipeline integration for advanced analytics use cases.
Prepare, manage, and optimize curated data sets within the data lake and data warehouse to support machine learning, forecasting, and advanced analytics initiatives.
Perform end-to-end data testing and validation to confirm the accuracy, completeness, and integrity of data delivered for analytics and reporting.
Ensure that the business intelligence and analytics platform is accurate, available, performant, and secure.
Diagnose, fix, improve, and automate complex issues across the data and analytics stack to ensure maximum uptime and performance.
Support data analysts by ensuring reliable data pipelines, data availability, and backend support for reporting and analytical models.
Participate in all phases of the analytics project process, including technical requirements gathering, design, development, testing, and implementation.
Provide well-documented data pipelines, infrastructure, and processes with attention to detail.
Responsible for identifying opportunities to enhance technology and innovation that will improve the effectiveness of the data and analytics platform.