Staff Analytics Engineer
Let’s Tango ! Where Innovation Meets Impact.
At Tango Analytics, we’re all about helping businesses make smarter decisions through powerful technology, insightful data, and a whole lot of collaboration. Whether you're a creative thinker, a strategic planner, a tech wizard, or a customer champion, there's a place for you on our team. We believe work should be meaningful and fun — so if you're ready to make a difference while enjoying the journey, come join us and let's Tango !
Role Summary:
We are looking for a Staff Analytics Engineer to be the most senior individual contributor on Tango 's Analytics Engineering team and the hands-on technical anchor for the modern analytics foundation we are building. You will design and build the governed semantic layer, the curated data models on our Redshift warehouse, and the Omni-based analytics that both our customers and our internal teams rely on. You will be prolifically hands-on: writing the models, defining the metrics, and setting the patterns the rest of the team builds on.
This role is central to our transformation. Tango 's analytics have historically been delivered the old way: bespoke, services-led custom reporting on a legacy Oracle BI stack. We have signed Omni as our new analytics layer and are building a modern data warehouse on Redshift underneath it. You will be the engineer who makes the new stack real, extracting business logic from legacy reports, re-implementing it as tested, reusable models, and standing up the semantic layer that makes every metric consistent across dashboards, embedded product surfaces, and AI.
Key Responsibilities:
Build and own the governed semantic and metrics layer
Design and own the semantic layer that is the single source of truth for Tango 's metrics. Define metrics once, in code, so they resolve consistently across every dashboard, embedded product surface, notebook, and AI query. Establish the modeling conventions, certification process, and documentation that keep the layer coherent as it grows and as more teams and agents consume it.
Model Tango 's data on the modern warehouse
Design and build curated, well-documented, tested data models on Redshift that turn a deep and complex real estate and facilities data model into analytics-ready datasets. Bring analytics-engineering discipline (version control, testing, CI/CD, lineage, and performance and cost awareness) and make it the standard the team works to.
Ship embedded, customer-facing analytics on Omni
Build the embedded, self-serve analytics experiences that live inside Tango 's product modules, replacing static exported reports with dynamic analytics customers can explore themselves. Handle multi-tenant isolation, performance, and per-customer variation as first-class engineering concerns so the experience is fast, correct, and safe across the base.
Make the data layer trustworthy for AI
Structure the semantic definitions, documentation, and lineage so that natural-language querying and Tango 's agents return correct, consistent answers rather than plausible guesses. Build the evaluation and quality checks that tell us when a model or metric is trustworthy enough for an agent to stand on, and treat the analytics layer as first-class, machine-readable context for AI.
Lead the Oracle BI to Omni migration, hands-on
Be the technical anchor of the migration off the legacy Oracle BI stack. Reverse-engineer and extract the business logic buried in existing reports, re-implement it as governed models and metrics, and drive a disciplined parallel-run so customers and internal consumers never lose the reporting they depend on during cutover.
Set the standard and level up the team
Create the reusable patterns, libraries, and review practices that make the whole team faster and more consistent. Mentor engineers and contractors as they move from legacy BI to modern analytics engineering, raise the craft bar through code and design review, and lead by example witho