Influence and oversee the enterprise data roadmap, scaling our data ecosystem as our data universe grows.
Define and enforce ETL/ELT standards for data ingestion, transformation, and loading across the organization.
Architect and manage cloud data infrastructure on AWS, including Redshift, DynamoDB, and scalable pipeline patterns.
Establish data cataloging, source system mapping, and data dictionary practices to organize our data universe.
Automate and streamline onboarding of third-party data sources as external service integrations expand.
Partner with analytics teams to support reporting and visualization needs using variety of tools including Tableau.
Collaborate with business partners on requirements gathering and advocate for effective data solutions.
Drive responsible adoption of AI and ML technologies, including LLMs (e.g., Claude, OpenAI), ensuring ethical use and data integrity.
Define and standardize the company’s ML tooling to enable high-value insights at scale.
Lead data governance efforts, including privacy protections, usage policies, and compliance standards.
Optimize query performance across relational and NoSQL database systems.
Evaluate emerging technologies and assess fit for Slate’s business and technical needs.

Bachelor’s degree in Computer Science, Data Engineering, or equivalent experience.
10+ years of experience in data engineering or a related technical discipline.
5+ years delivering production-grade data pipelines, data warehousing, and platform architecture.
Strong proficiency in AWS data technologies including Redshift, DynamoDB, and AWS Glue.
Deep knowledge of ETL/ELT best practices, pipeline orchestration, and optimization at scale.
Experience with BI tools such as Tableau and Power BI.
Familiarity with AI/ML platforms and LLM APIs; ability to apply them responsibly and ethically.
Experience with data governance, privacy regulations, and establishing data usage policies.
Proven experience with data cataloging, source-to-target mapping, and data dictionary creation.
Proficiency with relational (e.g., PostgreSQL, MySQL) and NoSQL (e.g., DynamoDB, MongoDB) databases, including query optimization.
Strong ability to translate business requirements into scalable data solutions and communicate effectively with non-technical stakeholders.
Automotive or OEM manufacturing experience is a plus.

Principal Data Engineer

Key skills