Senior Python Engineer - Data

Creospan is a growing tech collective of makers, shakers, and problem solvers, offering solutions today that will propel businesses into a better tomorrow. “Tomorrow’s ideas, built today!” In addition to being able to work alongside equally brilliant and motivated developers, our consultants appreciate the opportunity to learn and apply new skills and methodologies to different clients and industries.

******NO C2C/3RD PARTY, LOOKING FOR W2 CANDIDATES ONLY, must be able to work in the US without sponsorship now or in the future***

About the Role

This is the senior technical role on a data product team, in a data organization that is becoming a software-engineering organization and deliberately reinventing how engineering work is performed with AI.

You will be part of the team that builds APIs, backend services, shared libraries, operational data stores, and data-processing systems.

This is an individual contributor role with no direct reports. Each data product team operates through a three-way partnership: the product manager owns what gets built and in what order, the engineering manager owns the engineering practice and how engineers grow, and you own how it gets built, including the architecture, the interfaces, the sequencing of the work, and the call on whether a design is ready.

You will be measured by what the team ships, not solely by what you ship yourself. The best tech leads spend their time on decisions that are expensive to reverse and leave the rest to the engineers who will learn from making them.

The role sits at the seam between software engineering and data science and asks for real strength in both: you may not be building models yourself, but you need to be credible with the people who do, and able to reason about whether an offline metric will hold up online, what a latency budget means for an inference path, and when a model is the right tool and when a rule would do.

What You Will Do

• Stay in the code every week, and use AI throughout design, planning, implementation, testing, and review.
• Partner with your product manager on feasibility, sequencing, and trade-offs, early enough to change the plan.
• Partner with the Data Scientists and ML Engineers on your team, from problem framing through production serving, monitoring, and retraining.
• Design interfaces, service boundaries, schemas, and data contracts that other teams can rely on, and negotiate them with those teams.
• Participate design reviews and RFC discussions, and own the call on when a design is ready and on cross-cutting technical trade-offs.
• Grow the engineers around you through how you review, and partner with your engineering manager on where each one needs stretch or support.
• Own your team's operational health: on-call quality, observability, and the systems you have in production.

An Excellent Candidate Has

• Experience building production backend services, APIs, internal platforms, or distributed applications.
• Experience designing APIs, data contracts, and operational databases that other teams consumed.
• Familiarity with asynchronous processing, queues, event-driven systems, and change-data capture, including idempotency, retries, concurrency, and backward compatibility.
• Working knowledge of machine learning and data science concepts: feature engineering, evaluation, training and serving skew, drift, and retraining; enough to review a model design and ask the questions that matter, and experience taking a model from notebook to production.
• Comfort leading engineers who do not report to them, and partnering with a product manager whose priorities they do not set.
• Familiarity with cloud infrastructure, containers, CI/CD, infrastructure as code, and observability.
• Practical opinions about where AI tools are useful, where they are unreliable, and how to improve their output.

Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Applied Mathematics, Engineering, or a related field, or equivalent practical experience.
• Experience: Mid to senior level experience building production software
• Experience building, shipping, and operating production software, with strong programming skills beyond SQL.
• Hands-on keyboard every week, designing, building, and reviewing, not only directing.
• Strong grounding in both software engineering and machine learning or data science, and the ability to lead a technical discussion in either.
• A record of raising the team's output, delegating the decisions engineers will learn from, keeping the ones that are expensive to reverse, and deciding plainly when a design is ready.
• Influence without authority, earning alignment across teams, negotiating interfaces rather than escalating, and explaining a technical decision clearly to engineers, product managers, and leaders.