Senior Data Analyst

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• You will act as a liaison between the business (Product Owner, stakeholders) and the engineering team.

• Approximately 30% of your role involves hands-on data tasks: verifying that CDP functionalities operate as intended, exploring data prior to specifications being written, testing hypotheses for new features, creating shared gold layer models for consumer teams, and assisting those teams in understanding the available data.

• This role does not focus on business reporting or analytics tailored for individual brands.

• The remaining 70% is dedicated to Systems Analysis: translating findings into specifications that engineers can implement, ensuring data quality from symptoms to root causes, addressing issues before deployment, and designing the semantic layer to enable other business lines to locate and trust the data.

• Four key elements characterize the systems analysis aspect: Transform business needs into specifications that engineers can act upon. Engage with stakeholders, determine their true requirements, and document them. Each specification should detail source schema, target model, transformation logic, business glossary, schedule, data quality checks, consumers, and use cases.

• Maintain availability throughout development. Engineers will have inquiries. Identify and resolve data quality issues at their source, in conjunction with the engineering team.

• Track data lineage, ascertain causes, collaborate with data source owners for fixes, assess downstream impacts, and ensure the feedback loop is complete.

• Validate that delivered outputs meet the specifications you established. When discrepancies arise, raise them before deployment.

• Enhance data usability beyond the immediate requesting team. Contribute to the semantic layer, data descriptions, and shared definitions so other business lines can locate what they need, comprehend its meaning, and trust it without recurrent assistance from you.

• Your responsibilities will include working on the Data Platform layer: CDP construction, identity resolution, data quality, semantic definitions, and governance. Analyst teams aligned with specific brands will generate business analytics on top of the platform, including dashboards and performance reports. Your role is to ensure these teams can operate effectively: providing reliable data, clear definitions, and prompt issue resolution.

⛳️ Requirements

• SQL expertise is required. You should be proficient with window functions, complex joins, and root cause analysis on large datasets.

• Experience with dbt is necessary. You should be capable of writing models, performing tests, and debugging them.

• Proficiency in Python for ad hoc analysis, scripting, and data manipulation is expected.

• You should feel confident navigating the modern data stack. You should be able to independently troubleshoot issues instead of relying on Data Engineers, and communicate the root cause to the business in straightforward terms.

• Familiarity with medallion or layered data architectures is essential. You should have authored specifications that engineers utilized.

• You should have managed a data quality issue from initial observation to resolution at the source.

• You must be able to communicate effectively with both business stakeholders and backend engineers within the same hour without losing context with either party.

• A background in iGaming, affiliate marketing, SaaS, or other high-volume digital enterprises is preferred.

• Experience in unifying customer or user profiles across various sources, often referred to as Customer 360 or Single Customer View, is advantageous.

• Knowledge in areas such as identity matching and semantic modeling is beneficial.

🏝️ Benefits

• An opportunity to work on scalable, high-impact products within a growing iGaming business.

• A collaborative and fast-paced engineering environment.

• Exposure to modern technologies and architectural practices.