Senior Data Analyst - Commercial Data (Snowflake & SQL)

Our client is building an AI agent to support its field representatives. The agent’s recommendations depend directly on the accuracy, consistency and completeness of the underlying commercial data. We are currently facing data issues that affect the agent’s reliability, and we are looking for two experienced data professionals to diagnose and resolve them in close collaboration with the data engineering and data platform teams.

• Investigate and root-cause data issues affecting the AI agent (missing, duplicated, inconsistent, outdated or incorrectly mapped data).
• Write, optimise and maintain complex SQL queries in Snowflake to profile, validate and reconcile commercial datasets.
• Work hand in hand with data engineering, data platform and business data owner teams to define, prioritise and implement fixes at source or in the transformation layers.
• Define and implement data validation rules, checks and monitoring (completeness, accuracy, consistency, freshness) and report on progress and resolution KPIs.
• Translate business expectations from commercial stakeholders into data requirements and acceptance criteria.
• Document findings, issues, fixes and data definitions, and maintain a clear issue log with status and ownership.
• Support testing and validation of fixes, and confirm their impact on the agent’s outputs.

• Experience in data analysis or data engineering roles
• Strong hands-on experience with Snowflake (querying, data modelling concepts, performance optimisation).
• SQL skills (complex joins, window functions, CTEs, data profiling and reconciliation).
• Solid understanding of the pharmaceutical commercial domain: field force operations, CRM data (eg Veeva), HCP/HCO master data, customer segmentation and targeting, sales and market data (eg IQVIA), call activity and omnichannel engagement.
• Proven experience working with cross-functional data teams (data engineers, architects, product owners) to resolve data issues end to end.
• Strong analytical and problem-solving skills, with attention to detail.
• Excellent communication skills in English, able to explain technical issues to business stakeholders and business needs to technical teams.

Nice to Have

• Experience with data transformation and orchestration tools (eg dbt, Airflow, Informatica, Matillion).
• Familiarity with data governance, master data management and data catalog tools.
• Exposure to AI/ML or GenAI use cases and an understanding of how data affects model or agent performance.
• Experience in a large global pharma environment.
• Knowledge of GxP and data privacy considerations in pharma (eg GDPR).

Desirable Skills/Experience Although not essential, the following skills are desired by the client:

Soft Skills

• Proactive, hands-on and autonomous in a fast-paced programme.
• Collaborative mindset and strong stakeholder management.
• Structured approach to documentation and communication of findings.

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