Staff Data Engineer (m/f/d) at Buynomics

, , Germany -

Full Time

Start Date

Immediate

Expiry Date

01 Mar, 26

Salary

0.0

Posted On

01 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, MLOps, Python, Docker, ETL, Distributed Systems, Cloud-Based Data Processing, NumPy, Pandas, PyTorch, Scikit-Learn, Pydantic, Spark, Flink, Airflow, Dagster

Industry

Software Development

Description

About Buynomics: “What will customers buy?” is the crucial question underlying all commercial decisions in all companies. Buynomics has developed Virtual Shopper technology, which answers this question 100x faster and more precisely than every other solution. This will end the common practice of gut feeling. Our goal is to enable companies to make data-driven, transparent, and customer-centric commercial decisions. For that, we build the operating system for commercial decisions that provides companies with a single source of truth to answer all their market-facing questions including pricing, product offers, and promotions. Buynomics is the next-generation SaaS company in pricing and product optimization. It employs large-scale simulation technologies to digitize customers and predict their purchase behavior - in any environment. Our clients use Buynomics to make data-driven decisions about their current and new products, overall portfolio structure, pricing, promotions, trade terms, and more! Job Summary: We are looking for a Staff Data Engineer with strong experience in ML to join our team. In this role, you will shape the technical vision for our ML systems and act as a technical leader—designing production-grade pipelines, ensuring models are consistent, robust, and observable in production, and mentoring engineers. You will combine hands-on data platform expertise with MLOps, building the foundations that enable us to scale. You will also lead a small team of 3–4 engineers, guiding their work, setting technical direction, and fostering growth and collaboration. Responsibilities: Lead the design and development of end-to-end ML pipelines: training, validation, deployment, and monitoring. Define and enforce data and model contracts, versioning, and reproducibility standards. Build and operate feature stores, model-serving infrastructure, and drift detection frameworks. Design parallel ETL and data pipelines that transform raw inputs into clean, model-ready datasets with clear SLOs. Ensure reliability, lineage, and quality of datasets used in production ML workflows. Lead and mentor a small team, driving execution, performance, and career development. Review architecture and code, set technical standards, and mentor engineers across the team. Partner with Product, Data Science, and Engineering to translate requirements into scalable ML/data solutions. Drive operational excellence: monitoring, alerting, incident response, and cost/performance optimization. Requirements: 6+ years of experience building and deploying end-to-end ML solutions, ideally in a SaaS environment. Demonstrated ability to lead projects and guide engineers through strong technical leadership, complemented by experience in managing people and fostering team development. Proven track record of designing scalable, production-ready ML systems and pipelines. Strong expertise in MLOps, including experience with Docker, parallel ETL pipelines, distributed systems, and cloud-based data processing. Advanced programming skills in Python, with deep experience using ML libraries such as NumPy, Pandas, PyTorch, scikit-learn, and Pydantic. Hands-on experience with distributed compute frameworks (e.g. Spark, Flink) and workflow orchestration (Airflow, Dagster, Prefect). Preferred Qualifications: TensorBoard experience. Experience with large-scale simulation, forecasting, or optimization systems. Domain expertise in retail/CPG data, pricing, or revenue management. What we offer: Dynamic Environment: Join a truly international and diverse team where your ideas matter. Flexible work model: Remote-first with offices in Cologne — visits to HQ in Cologne roughly every 4-5 weeks, with flexibility. Learning Budget: Take advantage of our employee development and education budget to enhance your skills. Local Language Classes: Participate in language lessons to support your integration and personal development. Urban Sports Club Membership Deutschlandticket Personal and professional growth opportunities Regular company events To ensure a smooth and efficient process and that no applications are overlooked, please apply directly to the role. While we'd love to respond to everyone who reaches out, applying ensures that your application is properly tracked and considered. Buynomics is proud to be an equal opportunity employer. This means that we don’t discriminate based on race or ethnic origin, color, the language(s) you speak, where you (or your parents) are from, or whether or not you consider yourself to have a disability. Neither will your age, gender, gender identity, sexual orientation, religion, beliefs, or political opinions play a part in your application with us. We’re a diverse team in so many ways, and we love it that way. #LI-remote

Responsibilities

Lead the design and development of end-to-end ML pipelines, ensuring models are consistent, robust, and observable in production. Mentor a small team of engineers, guiding their work and fostering growth and collaboration.