Data Architect | Retail Analytics

2 weeks ago

London, Greater London, United Kingdom Appriss Retail Full time

About Appriss Retail

Appriss Retail empowers businesses to maximize profitability while effectively managing risk through real-time decision-making and active risk monitoring. Our solutions are constantly evolving to meet the dynamic demands of the retail landscape.

With over 20 years of expertise in retail data science, we serve a global network of leading commerce partners, representing one-third of all US omnichannel retail sales activity across 150,000 retail locations worldwide. Our solutions cater to diverse sectors including specialty, apparel, department stores, hard goods, big box retailers, grocery, pharmacy, and hospitality businesses in 45 countries across six continents.

Appriss Retail delivers compelling, relevant, and profitable collective intelligence to operations, finance, marketing, and loss prevention teams. Our performance-improvement solutions yield measurable results with significant return on investment.


About the Role

Data Engineers at Appriss Retail are integral members of a team that adheres to DataOps best practices. They own the standardized data assets and processes that underpin our products, empowering both our customers and internal teams.

The Data Engineer will develop and implement software programs, algorithms, and automated processes to cleanse, integrate, and evaluate vast datasets from diverse sources. They will analyze and assess the usability of customer-provided data and collaborate with product and service teams to identify questions and issues related to data quality. Furthermore, they will design, program, and implement methods, processes, and systems to consolidate and analyze diverse data sources, generating actionable insights.

What You'll Do

  • Develop and implement methods and processes for consolidating, normalizing, and analyzing data.
  • Construct robust and scalable data pipelines to map data into our data warehouse, which powers our various products.
  • Understand the data and implement quality checks.
  • Monitor and enhance toolsets/libraries.
  • Work with large datasets.
  • Present findings from these analyses to management and communicate issues to and from clients, coordinating the resolution of those issues.
  • Monitor the system's business performance, identify areas for improvement, and assist in identifying and tracking issues.
  • Collaborate closely with Support and Engineering teams to deploy and enhance products.
  • Participate in an on-call rotation.

Qualifications

  • Bachelor's degree in a field such as Statistics or Computer Science, or at least 2+ years of 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 datasets.
  • Experience with data warehouse solutions (VMWare Greenplum or Snowflake).
  • Excellent verbal and written communication skills.
  • Ability and willingness to work effectively within a team.
  • Proven ability to deliver on time-sensitive projects.

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