Senior Data Engineer (Contract)

Coconut Software is the leading Branch Performance Platform, helping financial institutions grow, drive productivity, and deliver better customer experiences.

Coconut's AI-powered, enterprise-grade platform brings together appointment scheduling, in-branch queuing, video banking, and branch workforce management, turning customer interaction and operational data into actionable insights across multiple lines of business. The result: greater visibility into performance, better use of workforce capacity, and smarter decisions that drive stronger branch outcomes.Trusted by 200+ banks and credit unions, including RBC, Mountain America Credit Union, and M&T Bank, Coconut Software turns every interaction and staffing decision into a competitive advantage.

We’re hiring a Senior Data Engineer on a 12-Month Contract to own data engineering on our Data Enablement team. You’ll be our main data engineer, working with our analytics engineers, product, and other enablement teams. You’ll build the pipelines behind our workforce forecasting and staffing product, and finish moving our analytics platform onto Databricks. We need someone who gets productive quickly, works independently, and leaves things better than when they found them!

Data at 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 target 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 find a better way to work • We work in a blameless culture and have a continuous improvement mindset • 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 ARE FIRED UP TO

• Build and run production pipelines in Databricks (Lakeflow, Jobs, dbt), from ingesting customer files through to tables ready for models and reporting • Lead the next phases of our Redshift → Databricks migration: landing source tables, moving product analytics onto the lakehouse, and retiring old warehouses • Own replication and ingestion from production databases (AWS DMS, Databricks Lakeflow Connect, Fivetran) across multiple environments, with data residency and PII handling built in • Set data contracts with internal teams and external ML partners so schema changes don’t break things downstream • Give product teams clear effort estimates and trade-offs, and push back on scope when needed • Monitor pipeline health, data quality and Databricks cost, and take part in Data’s on-call rotation • Document what you build (runbooks, lineage, design decisions) so the team can manage it without you (if needed) • Be part of how we’re evolving the way we work with AI across Engineering, staying curious about the technology and eager to adopt, learn, and use it to solve customer and business problems