Analytics Engineer

Spot & Tango is an innovative pet health & wellness brand that delivers personalized meal plans on a subscription basis. Our recipes are developed by leading animal nutritionists, and are made with only real, human-grade ingredients... and nothing artificial! We have lofty goals (to make every dog in the country healthier, and every pet parent happier!) and we are looking for the right people to help us get there. This is an exciting opportunity to join a VC-backed, high-growth, e-commerce startup and have an outsized impact in an extremely fast-paced environment. Plus, you get to think about dogs all day!

Who You Are:

You are a data-obsessed Analytics Engineer eager to be one of the first members of a new and growing data team. You are a confident analyst and are highly-proficient in data modeling; you are excited to explore multiple aspects of our business and build foundational datasets in a fast-paced startup environment. You are excited to wear many hats, and collaborate cross-functionally to answer a variety of business questions. You are comfortable using a variety of data technologies, especially dbt, SQL, Google BigQuery, and Looker, and are excited about learning new skills. You are comfortable with shifting priorities and can adapt to new + emerging business objectives.

Job Summary:

We are seeking an experienced and highly skilled Analytics Engineer to join our data team. As an Analytics Engineer, you will play a crucial role in driving data-driven decision making across the organization. Your expertise in data analysis, database management, and familiarity with tools like dbt, SQL, and Looker will enable you to design, develop, and optimize data models and pipelines to extract actionable insights for several teams within our company, including Product, Marketing, Operations, and Customer Success.

Responsibilities:

Data Modeling and Transformation: Collaborate with stakeholders to understand their analytical needs and translate these requirements into well-structured data models using dbt. Create tests for dbt models to ensure data quality and manage our daily dbt runs (via dbt Cloud).
Looker Development: Develop Looker views and explores allowing stakeholders to build dashboards, reports, and data visualizations. Create a BI environment that empowers stakeholders to access and interpret data easily. Implement best practices for Looker development to ensure consistency and standardization across the platform.
Data Analysis and Insights: Analyze complex data sets, identify trends, and extract meaningful insights. Collaborate with cross-functional teams to understand business needs and provide data-driven recommendations to drive decision-making.
Database Management: Manage and optimize our data warehouse (BigQuery) to ensure optimal performance and scalability. Write efficient and effective SQL queries to answer business questions.
Documentation: Document dbt models, Looker views/explores, and analytics queries to facilitate knowledge sharing and maintain an organized and accessible data ecosystem.

Requirements:

Education: Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
Experience: Proven experience as an Analytics Engineer with at least 1-2 years of experience in data modeling, business intelligence, and/or database management. Significant previous experience as an Analyst or similar analytics-minded role is a strong advantage. Experience with E-Commerce is highly preferred.
Technical Skills: (1) strong proficiency in SQL, (2) proficiency in using dbt for data modeling and transformation, (3) expertise in Looker and LookML for dashboard and report development, (4) experience with other Business Intelligence tools is also acceptable and desirable, experience with data warehousing and familiarity with cloud-based data platforms, esp. Google BigQuery, (5) not desired, but preferred: Knowledge of Python and experience with Airflow is a plus, as is familiarity with building and maintaining data pipelines.‍
Analytical Mindset: Demonstrated ability to analyze complex data sets, draw insights, and communicate findings effectively to both technical and non-technical audiences.‍
Problem-Solving Skills: Strong problem-solving and critical-thinking abilities with a passion for addressing business challenges using data-driven approaches.‍
Communication and Collaboration: Excellent communication skills with the ability to work collaboratively in a cross-functional team environment.‍
Continuous Learning: A self-motivated individual with a curiosity to stay updated with the latest trends, technologies, and best practices in data and analytics engineering.

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