Data Architect

The iGaming industry is becoming more and more demanding when it comes to data expectations. Therefore, it is becoming increasingly important to execute the most efficient architectures for our products.

As a Big Data Architect, you will be involved from the early stages of drafting technical solutions tied within the Big Data team within the Data Engineering Team. Throughout the software life cycle, you will draft architectures together with the Lead Big Data Engineer, Enterprise Data Architect and Lead BI to come up with the best possible architectures. You will also be involved in using your experience to size efforts of large tasks accordingly and this will be key for other key roles within the team.

Responsibilities

• Assesses as-is the current data platform, defines future state platform together with the BDE team lead. Performs gap analysis to drive the future state data platform (including implementation) with frequent discussions with internal parties such as the team lead, enterprise architect, data governance and data-devops.
• Understands leading/emerging Big Data technologies and trends on the market and can communicate these effectively to a wide audience.
• Clearly communicates any updates, new technologies or practises with the team lead and the BDE team in a clear manner.
• Ensures that the BDE adheres to best practices, this ensures that coding standards and the accuracy, validity, and reusability of data is maintained.
• Excellent working SQL knowledge and experience with both relational and columnar databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Collaboration with key stakeholders for specific research, work effort sizing.

Expected outcomes:

• Supports the team in refinement sessions to estimate better
• Supports the Lead Big Data Engineer to draft works that can be inclusive of all the team to avoid silos
• Provide input in project planning
• Supports team to be able to contribute to peer reviewing collectively

Data Design & Architecture

• Data modeling and schema design.
• Experience designing data warehouses, data lakes, and data schemas.
• Deep understanding of data flows, lifecycle, and enterprise data frameworks.

Databases & Data Management

• Proficiency in relational and non-relational databases (SQL, NoSQL).
• Strong hands-on knowledge of ETL/ELT tools, data integration, and data pipelines.
• Familiarity with data governance, lineage, and metadata management.

Cloud & Big Data Technologies

• Experience with cloud data platforms (AWS, Azure, GCP) and related services
• Understanding of modern data stacks and streaming technologies.

Security & Compliance

• Knowledge of data privacy, security frameworks, and regulatory compliance.
• Ability to design secure architectures and implement data protection strategies.