Who You Are: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 by creating and maintaining dbt models, pipelines, and other tools. Since we are a small data team, you will have the chance to work across our entire business - with members of our Operations, Strategy, Marketing, Product, Engineering, and Finance teams.
You are passionate about using data to uncover insights that drive a business forward - working with teams across that business to understand where data products can be deployed with the greatest effect.
You are a confident analyst and 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, python, Google BigQuery, and BI tools (we use Omni), and are excited about learning new skills. You are comfortable with shifting priorities and can adapt to new + emerging business objectives.
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).
- Pipeline and Model Maintenance: Monitor our pipeline and data model refresh jobs and triage issues if jobs fail. Help establish new pipelines (via a variety of tools including Portable, Fivetran, and airflow) when we need to ingest new sources of data.
- BI Development: Develop Omni views and topics, 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 Omni development to ensure consistency and standardization across the platform.
- Cross-Functional Collaboration: Partner with business and tech teams to identify data needs, translate business requirements into technical solutions, provide timeline expectations, and deliver actionable insights.
- Documentation: Document dbt models, pipelines, 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 strongly preferred.
- Experience: Proven experience as an Analytics Engineer with at least 3-4 years of experience in data modeling, business intelligence, and/or database management. Experience with E-Commerce is highly preferred.
- Technical Skills:
- Strong proficiency in SQL
- Proficiency in using dbt for data modeling and transformation.
- Experience with modern BI tools (e.g. Tableau, PowerBI, Looker, Sigma, Omni). Experience with Looker and Omni preferred.
- Experience with data warehousing and pipelines and familiarity with cloud-based data platforms, esp. Google BigQuery and Fivetran.
- Knowledge of Python and experience with Airflow is a plus.
- 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.
If you're passionate about data and dogs we encourage you to apply for this exciting opportunity!
This is a hybrid position.
You must be able to commute into our office in Midtown Manhattan Monday, Wednesday, and Thursday.