Build cloud-native, AI-ready data infrastructure and reusable data products for real-time analytics, data science, and AI-enabled solutions.

Design and engineer AI-native infrastructure for real-time data processing using optimal ETL patterns, frameworks, and query techniques
Develop semantic layers and knowledge graphs to support intelligent query routing and context-aware data access
Implement infrastructure for agentic AI systems, including multi-agent orchestration
Create GenAI-powered capabilities for data quality, entity resolution, and metadata management
Build and maintain data products across the lifecycle, from ingestion to consumption, in collaboration with the team
Deliver data products with clear SLAs, quality metrics, and customer satisfaction measures
Build self-service platforms that embed governance, lineage, and discovery
Establish data contracts and APIs for reliable, versioned data consumption
Develop high-quality pipelines that support analysts, data scientists, and AI agents
Implement CDC and event-driven architectures to enable real-time data availability
Use infrastructure-as-code with CDK and Terraform

Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience
2–5 years of overall relevant experience, including:
- Data warehousing
- Custom ETL design, implementation, and maintenance
- Object-oriented programming languages
- Schema design and dimensional data modeling
- Authoring SQL statements
Experience analyzing data to identify deliverables, gaps, and inconsistencies
Experience managing and communicating data warehouse plans to internal clients
BS/BA in a technical field, Computer Science, or Mathematics
Experience working with either MapReduce or an MPP system
Knowledge and practical application of Python
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact (efficiency gains, quality improvements)
Demonstrated ongoing AI skill development (prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Traditional medical, dental, and vision coverage
Generous 401(k) match
Paid Time Off: accrue up to 15 days in your first year; plus 40 hours of sick time and 3 personal days that refresh annually
Paid federal holidays
Special employee pricing on lending products such as mortgage, auto, and personal loans (eligibility subject to standard account requirements and underwriting criteria)

AI tools may be used to support parts of the hiring process, such as reviewing applications and analyzing information
These tools assist the recruitment team but do not replace human judgment
Final hiring decisions are made by humans

Data Engineer

Job Description