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Form of workAbout Appriss Retail
Appriss Retail provides real-time decisions and active risk monitoring to enable our customers to maximize profitability while managing risk. Our solutions are continually adapting to changing market conditions.
We bring 20+ years of retail data science expertise and experience. We serve a global base of leading commerce partners, representing 1/3 of all US omnichannel retail sales activity across 150,000 retail locations across specialty, apparel, department store, hard goods, big box, grocery, pharmacy, and hospitality businesses in 45 countries on six continents.
The company provides compelling, relevant, and profitable collective intelligence to operations, finance, marketing, and loss prevention. Appriss Retail’s performance-improvement solutions yield measurable results with significant return on investment.
About the role
Data Engineers at Appriss Retail are part of a team that follows DataOps best practices and owns the standardized data assets and the processes around it that support our products and enable our customers and internal teams.
The Data Engineer will develop and code software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources. They will analyze and evaluate the usability of data provided by customers and interact with product and service teams to
identify questions and issues for data quality. They will also develop, and program methods, processes, and systems to consolidate and analyze diverse data sources to generate actionable insights.
What you'll do
Develop and program methods and processes to consolidate, normalize, and analyze data.
Build robust and massively scalable data pipelines to map data into our data warehouse that powers our various products.
Understand the data and implement quality checks.
Monitor and improve toolset/libraries.
Work with large datasets.
Present results from these analyses to management and communicate issues to and from clients, and coordinate resolution of those issues.
Monitor the system’s business performance, identify areas for improvement and assist in the identification and tracking of issues.
Interacts closely with Support and Engineering teams to deploy and improve the products.
- Participate in on-call rotation.
Qualifications
Bachelor’s degree in an analytical related field such as Statistics or Computer Science or at least 2+ years equivalent professional experience.
Experience with SQL (2+ years)
Proficiency with Python (2+ years)
Ability to work with APIs, structured and unstructured data.
Experience processing and analyzing large data sets.
Experience with data warehouse solutions (VMWare Greenplum or Snowflake).
Good verbal and written communication skills.
Ability and willingness to work with a team.
Proven ability to work on time-sensitive deliverables.
