Design, implement, and maintain data pipelines and workflows to support AI and analytics use cases
Manage and optimize structured and semi-structured data using MySQL, Redshift, OpenSearch, and related datastores
Evaluate and implement new database technologies and AWS-native tools to support scalability and performance
Collaborate with data scientists, engineers, and product managers to ensure data needs are met across systems
Build internal tooling for data access, transformation, and quality monitoring
Support infrastructure-as-code and cloud automation to maintain high system reliability

3+ years of experience in data engineering or related backend/infrastructure roles
Proficiency in working with relational and non-relational datastores (e.g., MySQL, OpenSearch)
Strong experience with AWS tools such as S3, Glue, Lambda, or similar
Experience building and maintaining ETL/ELT pipelines and working with structured and unstructured data
Experience with Python for data processing (pandas, PySpark, or similar)
Comfort with contributing to production codebase
Familiarity with containerization (e.g., Docker) and version control (e.g., Git)
Must pass FBI fingerprint and background check in multiple states.
Nice to Have:
Experience supporting ML/AI pipelines or working closely with data science teams
Experience with Sisense or similar embedded BI/analytics platforms
Knowledge of DBT or similar SQL transformation frameworks
Familiarity with infrastructure as code tools (e.g., Terraform, CloudFormation)

Data Engineer

Key skills