If you are a current employee who is interested in applying to this position, please navigate to the internal Careers site to apply.
The AI and Data Operations team is responsible for providing accurate, timely, well-structured data to AI Engineers, Business Intelligence Engineers, and management teams. As a Data Engineer, you will build and maintain data repositories, custom workflows, data integrations, and imports. You will work closely with Business Intelligence and AI Engineers to create shared data models they can use to drive value for the business.
- Monitor data processes, workflows, and jobs, and address any issues that arise
- Leverage SQL, Python, Azure tools, PowerBI, and other technologies to extract, transform, and load data into well-designed data models
- Understand and follow all rules and procedures required by security and best practice policies
- Document data models and software, and clearly communicate current state and changes to the teams that use them
- Document metadata in a centralized repository in a way that allows us to maximize the value of the data we manage
- Work with public and private APIs, file stores, databases, and other repositories to enhance and expand data capabilities
- Write highly resilient, high throughput data workflows with solid logging and process monitoring
- Import and integrate data into front line systems for MarketStar corporate and client teams
- Actively engage with the team while working in a remote environment, working to deliver an excellent level of service to all consumers of the data
- Create and maintain highly reliable APIs that expose data and AI services to other teams
- Constantly improve yourself and the team through training and sharing of best practices
- Understand MarketStar’s business processes and make suggestions on data services that could drive value for the business
Preference given to candidates with
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or similar field
- A willingness to learn new tools and technologies
- Experience querying data using the SQL language
- Experience working with data using the Python language
- Experience creating and sharing data models/data marts/data warehouses
- Experience working with APIs
- A high-level understanding of sales processes and tools
- Solid communication skills with experience translating complex technical processes or problems to non-technical language
- Experience in measuring, reporting, and analysis of processes.
- Understanding of agile project/task management techniques.