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Role Description

We’re looking for a Senior Data Engineer to help shape and scale our modern data platform. This role combines hands-on technical ownership with strategic influence across our data ecosystem. You’ll work with AWS serverless technologies, Snowflake, dbt, and Terraform to design reliable, scalable, and cost-effective data pipelines that empower analytics and AI-driven applications.

You’ll play a key role in building the foundation that allows us to make smarter, faster, and data-driven decisions while also enabling AI-powered products and insights.

• Design, build, and maintain cloud-native data infrastructure using Terraform for IaC.
• Develop and optimize data pipelines leveraging AWS services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora, etc.) and Snowflake.
• Implement ELT workflows within dbt in partnership with our Analytics Engineering function.
• Build and maintain LLM frameworks, ensuring high-quality and cost-effective outputs.
• Automate infrastructure and pipeline deployments with CI/CD best practices.
• Monitor, debug, and improve system performance with strong observability and logging practices.
• Partner with cross-functional teams (analytics, data science, product, engineering) to deliver high-quality data solutions.
• Mentor teammates and contribute to engineering standards, raising the technical bar across the team.

Qualifications

• 5+ years of professional experience in data engineering or software engineering, with emphasis on scalable data systems.
• Deep experience with AWS cloud services (especially Lambda, Fargate, Step Functions, S3, DynamoDB, Aurora).
• Hands-on expertise in Terraform and/or AWS CDK for managing infrastructure as code.
• Strong knowledge of SQL and experience with Snowflake or another cloud data warehouse.
• Proficiency with dbt and modern ELT patterns.
• Solid coding skills in Python (or another general-purpose language).
• Experience building pipelines to support AI/ML workflows (feature engineering, training data pipelines, model monitoring).
• Understanding of CI/CD workflows, Git-based development, and containerization (Docker).
• Knowledge of data quality, governance, and observability best practices.

Requirements

• Experience in both startup and enterprise environments, with ability to adapt to fast-changing priorities while maintaining quality.
• Familiarity with orchestration frameworks (Airflow, Dagster, Prefect).
• Knowledge of streaming/event-driven architectures (Kinesis, Kafka).
• Prior experience mentoring or leading engineers.

Benefits

• We hire based on ambition, grit, and a passion for improving the way people work.
• We assess every candidate based on the potential impact they can have.
• We hire the best people for the job and support each person’s journey to build their boldest career.