What you'll do:
- Tableau Design: Design and build highly interactive dashboards that guide users through a clear narrative flow. You don’t just display data; you highlight trends, anomalies, and actionable insights.
- UX/UI Strategy: Apply design best practices (layout, color theory, pre-attentive attributes) to ensure dashboards are intuitive, consistent, and reduce cognitive load.
- Performance Tuning: Proactively monitor and optimize both SQL queries and Tableau workbooks to ensure fast load times and a seamless user experience.
- Data Modeling: Own the design and optimization of dimensional data models (Star Schemas) in BigQuery to create a clean, accessible, and performant "semantic layer" for analytics.
- Pipeline Development: Design, build, and maintain scalable ELT / ETL pipelines (using SQL, Python, and orchestration tools) to transform raw data into analytics-ready datasets.
- Data Quality & Governance: Establish and advocate for data integrity by implementing automated testing, validation frameworks, and consistent metric definitions.
- Internal Consulting: Act as a trusted advisor to stakeholders. Translate vague business questions into strict technical requirements and analytical stories that get to the root of the problem.
- Mentorship: Foster a culture of data literacy by mentoring business users on dashboard interpretation and training junior analysts on SQL best practices.
- Documentation: Maintain clear technical documentation for data lineages, metric definitions, and pipeline logic.
What you need:
- Experience: 4+ years of hands-on experience in a hybrid data role (Analytics Engineer, Data Engineer, or BI Developer).
- Advanced SQL & Modeling: Expert-level proficiency in SQL. You must be comfortable writing complex CTEs / window functions and have a strong grasp of Dimensional Modeling (Kimball methodology).
- Tableau Proficiency: Deep proficiency with Tableau Desktop. You must have experience with advanced calculations (LODs, Parameters, Set Actions) and a strong understanding of layout strategies to guide user attention.
- Python & Scripting: Strong experience using Python for data manipulation, API calls, and automation scripting.
- Data Storytelling: Proven ability to demonstrate how you have taken a raw dataset and turned it into a clear business recommendation or narrative.
- Modern Data Stack: Experience working within a modern cloud ecosystem (e.g., GCP, AWS, Azure) and cloud data warehouses (BigQuery, Snowflake, Redshift).
- Communication: Excellent verbal and written skills; you can present a dashboard to a stakeholder and clearly articulate the business value.
- Education: Bachelor’s degree in Computer Science, Engineering, Mathematics, Information Systems, Design, or a related field.
