Design, build, and maintain end-to-end ETL/ELT data pipelines for batch, real-time, and unstructured data using Python and Snowflake.
Develop and optimize data architectures for scalability, low latency, reliability, and cost efficiency in cloud environments.
Build and manage feature stores and reusable data and feature functions that support machine learning model and decision framework development.
Deploy data and analytics solutions to Amazon Web Services (AWS) using CI/CD automation and DevOps best practices.
Implement robust data quality controls, validation checks, monitoring, and alerting to ensure production-grade pipelines and data products.
Own end-to-end data product lifecycle, including requirement gathering, solution and architecture design, stakeholder validation, deployment, and performance tracking.
Conduct analytics and support development of machine learning and predictive model pipelines and frameworks.
Create and maintain clear technical documentation and collaborate within Agile workflows using tools such as JIRA and Confluence.

4 years of experience in data engineering or data analytics building production-grade data pipelines and data products using Python and SQL in a commercial environment.
4 years of experience developing and optimizing data solutions on cloud platforms, including hands-on experience with AWS and Snowflake in a data engineering context.
4 years of experience building scalable, low-latency systems or feature components supporting analytics, machine learning, or decisioning use cases.
Experience with CI/CD automation and DevOps practices to deploy, monitor, and support data solutions in production environments.
Experience working in Agile delivery environments using tools such as JIRA and Confluence or similar work-tracking and collaboration platforms.
Demonstrated experience in collaborating with internal and external stakeholders and drive initiatives using excellent verbal and written communication skills.
Bachelor’s degree or higher in Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field, or equivalent combination of education, related experience and/or military experience.

Fuel Your Life program to support your physical, financial, social, and emotional well-being.
Paid holidays and generous time away policies.
No-cost mental health support through Employee Assistance Programs.
Living Proof program to recognize your peers’ extra effort with points redeemable for rewards.
Eight Employee Resource Groups to foster a collaborative culture and expand your network.
Unparalleled professional growth with training, development, and internal mobility opportunities.
Medical, dental, vision, life, and disability insurance options available from day one.
Retirement planning and discounted shares with the Employee Stock Purchase Plan.
Tuition assistance and reimbursement program.
Paid parental, caregiver, and military leave.

Senior Data Engineer, Analyst

Key skills