Analytics Engineer

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October 14

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Smeetz

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SaaS • B2B • AI

Smeetz is a company that provides an AI-powered commerce intelligence hub designed to transform visitor attractions. They offer unified commerce solutions to simplify ticketing and in-store sales operations for amusement parks, zoos, aquariums, museums, heritage sites, and live venues. Smeetz helps businesses maximize sales and conversions through dynamic pricing and AI-based cross-selling strategies. Their platform also includes marketing intelligence to enhance visitor experiences with personalized offers and performance insights to optimize operations. Smeetz is trusted by various leading attractions to improve visitor management and increase revenue.

11 - 50 employees

☁️ SaaS

🤝 B2B

📋 Description

• Design, build, and maintain scalable and reliable data models within our data warehouse (Google BigQuery) using dbt to power business intelligence and analytics. • Develop and own key business intelligence dashboards and reports in our BI tool (e.g., Looker, Tableau, Metabase), providing actionable insights to stakeholders across sales, operations, and product teams. • Collaborate with business stakeholders to understand their needs, translating complex questions into technical requirements and analytical projects. • Analyze large, complex datasets to identify trends, opportunities, and performance drivers, delivering clear and compelling findings. • Ensure data integrity and quality by developing data validation tests, documentation, and monitoring our core data pipelines and models. • Build the foundational data infrastructure that empowers self-service analytics and prepares Smeetz for future data science and AI initiatives.

🎯 Requirements

• Experience: 2+ years in a data analytics, business intelligence, or analytics engineering role. • Core Technical Skills: • SQL: Expert-level proficiency in SQL for complex querying and data manipulation. • Data Modeling & Transformation: Proven, hands-on experience with dbt (or a similar data transformation tool) for building modular and tested data models. • Data Warehousing: Experience working with a modern cloud data warehouse, preferably Google BigQuery (experience with Snowflake, Redshift, etc., is also valuable). • Business Intelligence: Proficiency in creating insightful dashboards and reports using a BI tool like Looker, Tableau, Power BI, or Metabase, etc. • Programming & Workflow: • Familiarity with Python (especially Pandas) for data analysis and scripting is a strong plus. • Experience with version control systems, particularly Git, is required. • Analytical Mindset: Strong analytical and problem-solving skills, with experience in statistical analysis and A/B testing methodologies. • Communication: Excellent ability to communicate complex data insights clearly and concisely to both technical and non-technical audiences. • Bonus Points for: • Experience with data pipeline orchestration tools (e.g., Airflow, Dagster, Prefect). • Prior experience in a SaaS, e-commerce, or a fast-paced tech environment.

🏖️ Benefits

• Competitive salary based on experience. • Fully remote position, allowing you to work from the comfort of your own space. • Opportunities for professional development and career growth. • Collaborative and inclusive team culture.