Bespot provides location fraud detection and deep location intelligence solutions for the retail and hospitality industries, satisfying the needs of both small stores and larger facilities.

The company offers location-based white-label mobile services and a location positioning SDK that uses Machine Learning techniques to determine users’ location in indoor and outdoor environments accurately. Bespot SDK achieves world-class indoor location accuracy.

Leveraging first-party location data, transactional and other company data, bespot’s insights platform assists companies in unlocking valuable insights about shoppers. We are giving access to footfall trends, live heatmaps, customer personas, consumer preferences, and other insights regarding brick-and-mortar stores and brands.

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WHAT WE NEED

We are looking for a mid-level Data Engineer to join our team, who will be responsible for designing, building, and maintaining our data infrastructure, as well as optimizing data flow and collection for cross-functional teams.

 

WHAT YOU'LL BE DOING

• Design, build and maintain our data infrastructure, including ETL processes, data pipelines, and data warehouses.
• Collaborate with cross-functional teams to identify data needs and build data solutions that meet business requirements.
• Develop, maintain, and optimize data pipelines to ensure timely and accurate data delivery.
• Ensure data quality and integrity through data profiling, testing, and validation.
• Design and implement scalable data storage solutions.
• Monitor and troubleshoot data pipelines, and work with relevant teams to resolve issues.
• Stay up to date with emerging data technologies and trends, and recommend ways to improve our data infrastructure.

Skills and Qualifications:

• Bachelor’s or Master’s degree in computer science, or engineering or in any relevant field
• 2+ years of experience in data engineering or a related field

• Strong knowledge of database design, data modeling, ETL processes, and data warehousing

• Experience with Big Data technologies and related tools (e.g., Spark)

• Knowledge of code (e.g., Python, Java)

• Experience working with large datasets and developing data pipelines

• Strong problem-solving and analytical skills

• Excellent communication and collaboration skills

• Experience with cloud infrastructures/tools will be positively considered

• Flexible working hours, ability to work from anywhere;
• Welcome kit including equipment;
• 20% extra paid leave;
• Private health insurance plan;
• Sponsored conference and seminar attendance;
• Access to resources for professional and personal development;
• Snacks, coffees, and drinks on us.
• Stock option plan