At Coconut Software, we’re not just building data pipelines, we’re architecting the source of truth that powers the future of financial connections. As a Senior Analytics Engineer, you will be the glue between our technical data infrastructure and our business outcomes. While your primary focus is building a world-class modeling layer in dbt and Looker, you are equally comfortable putting on your Data Analyst hat to help stakeholders uncover the "why" behind the numbers.

Your role extends beyond technical modeling; you will be a mentor, a guide, and an advocate for data best practices. You’ll help foster an inclusive, psychologically safe environment where data professionals can do their best work. By proactively improving our data modeling standards and strengthening cross-functional collaboration, you will ensure our team delivers high-quality, actionable insights that meet both user needs and business goals.

Data @ Coconut:

• We are currently in an exciting phase of growth, migrating our entire data estate from legacy Postgres and Redshift environments to a modern Databricks Lakehouse.
• Our stack is built for scale: Databricks for storage and compute, dbt for our transformation and semantic layer, and Looker (LookML) for business intelligence.
• We don't follow rigid Scrum, but we do work in an agile, iterative way, and try to continuously improve and implement what works for us.
• We work in a blameless culture and have a continuous improvement mindset.

[Note: On Call] We strive to provide service excellence in all areas, as such, roles in our Engineering department are expected to contribute to our collaborative on-call rotation, working with your team to support our systems and ensuring application availability/reliability. Each team will have their own rotation schedule.

YOU’RE FIRED UP ABOUT:

Team Elevation

• Mentor and support data analysts, data engineers and developers, fostering a collaborative and psychologically safe environment.
• Set high standards for technical excellence in SQL, dbt modeling, and LookML architecture.

Technical Delivery & Ownership

• Collaborate with other analytics engineers on the migration of legacy logic from Redshift/Postgres into performant Databricks silver and gold layers.
• Independently implement complex data models in dbt, demonstrating expertise in modularity, testing, and performance optimization on Spark.
• Own the LookML layer, ensuring our explores and dashboards are performant, intuitive, and accurate.
• Act as a "Hybrid Analyst," comfortably balancing long-term engineering projects with ad-hoc requests to support the business. 
• Translate stakeholder questions into Looker-based reports and visualizations, ensuring the business has the right insights at the right time.

Data Architecture & System Design

• Lead technical data planning through discovery, design, and release, ensuring clear documentation for data catalogs and version tracking.
• Identify opportunities for "data debt" reduction and architectural improvements in our Lakehouse and semantic layers.
• Proactively address system characteristics like latency and throughput, ensuring our data pipelines are optimized for cost and speed.

Product and Business Partnership

• Act as a subject matter expert in your data domain, contributing to business strategy to ensure we are measuring what matters.
• Provide engineering perspectives on the product roadmap, clearly communicating data feasibility and reporting limitations.

WHAT YOU BRING TO THE TEAM:

• 5+ years of applied experience in an Analytics Engineering or Data role with a solid track record of technical leadership in B2B/SaaS environments.
• Extensive experience architecting dbt projects and managing complex Looker environments.
• Solid experience using Looker (or similar BI tools like Tableau or Power BI) to build dashboards and solve complex data requests.
• Strong architectural understanding of modern data stacks, with proven experience in Databricks.
• Expertise in writing, improving, and troubleshooting complex SQL queries.
• A passion for learning and exploring how AI/LLMs (like Google Gemini) can be integrated into the data lifecycle.
• The ability to successfully collaborate cross-functionally, gathering requirements and delivering results to different teams and departments.
• Excellent interpersonal and communication skills; you can relay complex technical ideas to anyone in the building

This posting is for a vacant position. The expected hiring range for this role is $120,000 - $160,000.

The base salary for this position is listed to support candidates to align themselves within the target range. The range is grounded in comprehensive analysis of national compensation data for similar roles and company sizes in the technology sector, alongside a review of our internal compensation framework to ensure pay equity across the company. Note that ranges may evolve over time.  We aim to provide a fair offer and hire within this specified range. The final offer for this position will take a candidate's background, experience, skills, and internal equity into consideration. Top performers’ compensation will be reviewed annually, as part of our Performance Acceleration program (Performance Reviews, Compensation Reviews, etc.).