Senior Data Analyst (Python / SQL / dbt)

About the project

Join an international data project built around social media trend signals. You will shape how trends and hashtags from TikTok and other social platforms are detected, scored and mapped to new industry verticals, and lead the evaluation of new data sources such as Reddit. This is a hands-on role focused on data, metrics and signal quality, not on building dashboard UI.

🎯 What you will do

• Own the technical approach for extracting, analysing and scoring trend signals and hashtags from social platforms.

• Evaluate new social data sources, starting with Reddit, and assess their value for the project.

• Define, validate and refine analytical metrics.

• Build quick prototypes and prototype pipelines to validate ideas with stakeholders before full implementation.

• Turn ambiguous business and product requirements into clear technical plans.

• Clean and prepare large datasets, with automated tests built into pipelines to ensure quality and reliability.

• Deliver clean, reusable code, datasets and pipelines, documented and tracked in Jira.

• Work closely with senior data leadership and help shape the technical direction of the workstream.

📌 What we expect

• 5+ years of commercial experience as a Senior Data Analyst, Analytics Engineer or in a similar role.

• Strong Python and SQL.

• Hands-on commercial experience with dbt.

• Experience with Snowflake.

• Experience with large datasets, data preparation and data quality.

• Proven ability to solve complex, ambiguous problems independently and take full ownership of delivery.

• Experience with Git/GitHub.

• Proficient use of AI coding tools (e.g. Copilot, Cursor, Codex, Claude Code) while staying fully accountable for the quality of the output.

• Very good English.

➕ Nice to have

• Experience with social media, web, trend or behavioural data.

• Experience evaluating and integrating new external data sources or APIs.

• Airflow.

• Data Vault modelling.

• Tableau and/or Power BI.

💡 Why join us

• Fully remote work and a quick start.

• Real influence on technical decisions and approaches.

• Large, diverse social media datasets and new data sources to explore.

• Modern data stack: dbt, Snowflake, Airflow, Python.

• Close collaboration with senior data leadership.

• Multisport card.

• Private healthcare.