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

📋 Description

• Take ownership of processes from start to finish: design, implement, test, deploy, monitor, and provide support in a production environment.

• Develop and maintain ETL pipelines utilizing both scheduled and event-driven batch processing to handle extensive volumes of web, behavioral, and account data.

• Manage the team's infrastructure, CI/CD, and observability, including the integration of legacy systems into the modern platform.

• Ensure the accuracy of the data generated by systems, actively preventing unnoticed data issues.

• Make critical technical decisions, write tests that reflect actual business logic, and conduct thorough code reviews.

• Deploy and manage work directly in production and address any issues that arise.

⛳️ Requirements

• Senior-level experience: a proven history of building and maintaining production systems, capable of independently managing products from start to finish.

• Proficient in Python, with expertise in both data-processing and service/API environments.

• Knowledge of SQL and cloud data warehousing (such as Snowflake or equivalent), along with a strong instinct for data accuracy and idempotency.

• Experience with event-driven architecture on AWS (including SQS/SNS, S3, IAM, Secrets Manager), with workloads managed in Docker and Kubernetes.

• Familiarity with a workflow orchestrator (such as Argo Workflows, Airflow, Dagster, or similar).

• Demonstrated operational maturity: you implement monitoring in your builds and are capable of diagnosing production issues independently.

• Effectively collaborate within a small cross-functional team and communicate technical trade-offs to data science and product stakeholders.

• Experience with infrastructure as code (using Pulumi or Terraform) is a plus.

• Familiarity with deploying ML models in production, including transformer inference, vector databases, GPU scheduling, and LLM APIs, is advantageous.