Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and take ownership of the data pipelines and machine learning services that determine product eligibility and support downstream decision-making throughout Flex.

• Model the data ecosystem (including products, merchants, eligibility criteria, classifications, and outcomes) within warehouses and serving systems created by other teams.

• Collaborate with backend developers, product managers, and operations stakeholders to translate the needs of merchants and consumers into dependable data products, models, and APIs.

• Take responsibility for enhancing the architecture of the data warehouse, transformation layer, machine learning training and inference systems, as well as real-time serving paths.

• Analyze, troubleshoot, and rectify production issues related to data quality, model performance, pipeline reliability, and serving latency.

• Work on cross-functional initiatives that connect the complete Flex experience, ranging from consumer checkout to merchant analytics.

• Construct and maintain evaluation harnesses, golden datasets, and observability for the models and pipelines you deploy.

• Develop and sustain documentation for data models, pipelines, and on-call runbooks.

• Foster a culture of learning, problem-solving, and operational excellence.

⛳️ Requirements

• Over 5 years of experience in building production data systems and pipelines using Python or a similar typed language.

• Strong foundation in SQL and data modeling; familiarity with a modern cloud data warehouse (such as Snowflake, BigQuery, Redshift, or similar) and a transformation framework like dbt.

• Practical experience in deploying machine learning models into production, managing training, inference, evaluation, and rollout—not solely limited to notebooks.

• Knowledge of at least one transformer-based machine learning framework (preferably PyTorch with Hugging Face Transformers) and an understanding of when classical or embedding-based models outperform LLMs and vice versa.

• Resourceful, inquisitive, and quick to learn new tools.

• Flourish in fast-paced, dynamic environments and enjoy taking on multiple roles.

• Collaborative and eager to work across teams to address challenges.

• Execution-driven with a focus on end users.

• Skilled in utilizing AI tools to accelerate delivery.

🏝️ Benefits

• Medical, dental, and vision insurance plans.

• Unlimited paid time off and sick days.

• Paid parental leave.

• Flexible, remote-first work environment.