Grasshopper Bank

Compensation

Full Description

Analytics Data Engineer Department: Data Employment Type: Full Time Location: Remote Description Grasshopper Bank is a client-first, digital bank built for the business and innovation economy, with an obsession for providing leading-edge technology, solutions-driven products and superior service through a combination of passionate people and digital resources. We are a highly experienced team who pride ourselves on diversity of thought and perspective. Nationally chartered, our portfolio of products and services range from VC, PE & Portfolio Companies to SBA Lending, as well as direct SMB and Embedded Banking. Our entrepreneurial drive allows us to support the growth and success of a wide range of clients at every stage of their business through inclusive partnership. We seek out team members who will enable both our organization and our people to grow and thrive through collaboration and acting with integrity and respect. Our focus on cross-functional teamwork provides a culture where ideas are valued, accountability is encouraged, and successes are celebrated. We welcome all those searching for the opportunity to contribute to banking innovation that influences and supports the emerging digital world of Financial Services. Our digital first approach enables our teams the flexibility to work remotely. We have offices in NYC and Boston. What you'll do: Reporting to our Director of BI & Analytics, you will join our data team as a key internal consultant and technical expert. Whether you are a seasoned architect or a rising talent in the analytics space, your primary mission is the same: to move beyond simple reporting and transform complex data into compelling data stories. This is a high-impact role where technical rigor meets design strategy. You will serve as the bridge between our data infrastructure and our stakeholders, owning the end-to-end data lifecycle. This includes architecting scalable data models and ELT pipelines, as well as partnering directly with business lines to build polished, intuitive Tableau dashboards. If you are a versatile professional who enjoys both writing complex Python/SQL transformation logic and crafting data stories that answer the "so what?" for leadership, we encourage you to apply. Responsibilities include: Visualization & Storytelling 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 Engineering & Architecture 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. Strategy & Consultation 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.