Job Description
Job DescriptionTITLE: Senior Data Engineer
LOCATION: Remote based with approximately 5% travel required.
REPORTS TO: VP of Technology
KEY RELATIONSHIPS AND TEAM: This role will report to the Vice President of Technology and will work in close partnership with the Architecture, Engineering leadership, and the Product organization to establish the foundation for F&I Sentinel’s next-generation data ecosystem.
THE OPPORTUNITY: F&I Sentinel is building the next generation of data infrastructure to power the industry’s trusted source of truth for all automotive F&I transactions. We’re seeking a highly skilled and experienced Senior Data Engineer to lead the design and implementation of a unified data layer that connects our relational and NoSQL systems into a scalable, high-quality data platform supporting analytics, compliance, and product functionality. This role is crucial for developing a unified, canonical data model and enabling advanced AI and semantic capabilities across the organization. The ideal candidate will possess deep technical expertise, strong leadership skills, and a passion for transforming complex data into a usable format for insights and decision-making.
Specifically, Senior Data Engineer will have responsibility in:
- Provide a robust foundation for analytical and operational data needs: Architect, design, and implement end-to-end data platforms, including data warehouses, data lakes, and streaming solutions that provide a scalable and reliable foundation to support both analytical and operational workloads across the organization.
- Deliver trustworthy and timely data to downstream consumers: Build, optimize, and maintain scalable data pipelines and ETL/ELT processes that ensure accurate, timely, and reliable delivery of data from diverse systems (relational and NoSQL sources) to downstream consumers and business applications.
- Maintain scalable and efficient data storage solutions: Develop and manage canonical data models and semantic layers that streamline storage structures, eliminate redundancies, and ensure consistency, scalability, and efficient access to enterprise data assets.
- Ensure high data quality and governance across the organization: Implement comprehensive data quality, validation, and governance frameworks that monitor integrity, security, and compliance with internal standards and external regulations (e.g., SOC2, lender audits, and reporting requirements).
- Optimize data infrastructure for performance and cost: Continuously monitor and tune data systems and workflows for optimal performance, observability, and maintainability—identifying and resolving bottlenecks to deliver high-speed, cost-effective data processing and retrieval.
- Safeguard data assets and ensure compliance with regulations: Collaborate with architecture and security teams to design secure data ingestion and storage patterns, enforce data privacy and access controls, and ensure adherence to industry and regulatory standards across all environments.
- Empower analytics teams with reliable and accessible data: Develop automation tools, semantic layers, and self-service analytics frameworks that enable analytics and business teams to easily access, interpret, and leverage high-quality data for decision-making, while mentoring engineers on best practices.
Professional Qualifications:
The following knowledge, skills, education, and experiences are required:
- Bachelor's degree in Computer Science/Engineering/Information Systems, or a related technical field.
- 7+ years of experience as a Data Engineer or as a Backend developer in a production environment, with a heavy emphasis on design, development, and data integration. Prior experience in building data foundations from scratch or modernizing legacy hybrid data environments preferred.
- Programming Languages: Strong proficiency in programming languages such as Python or other scripting language, as well as advanced knowledge of SQL is essential for data manipulation, automation, and working with nig data frameworks.
- Database Expertise: Hands-on experience with both relational database management systems (OLAP and OLTP) and NoSQL databases. Strong experience with data pipeline tools (Airflow, Fivetran, dbt, Prefect, Dagster, or equivalent).
- Big Data Technologies: Experience with big data frameworks and technologies such as Hadoop, Spark, Apache Kafka, and related cloud services (e.g., AWS EMR, Azure Data Factory, etc.).
- Cloud Platforms: Proficiency with major cloud platforms (AWS, Azure, or GCP) and their data service offerings (e.g., S3, Redshift, BigQuery, Snowflake).
- Analytics and BI tools: Experience integrating with one more cloud-based BI tools such as Domo, Power BI, ThoughtSpot, Qlik
- Data Modeling: Strong understanding of data modeling principles, database design (normalization and schema design) both operational and analytical workloads, complex data models (e.g., Kimball, Inmon, Data Vault), and data warehousing concepts.
- DevOps and CI/CD: Familiarity with DevOps practices, version control systems (like Git), and orchestration tools like Apache.
- Semantic & AI Knowledge: Familiarity with AI/ML concepts and experience in building data pipelines that support machine learning models and semantic data access.
- Data Governance: Familiarity with data governance and compliance frameworks (SOC2, GDPR, audit evidence management).
- Problem-Solving: Excellent problem-solving, analytical, and critical thinking abilities.
- Communication: Excellent communication skills to work effectively within cross-functional teams and present technical information to non-technical stakeholders.
The following knowledge, skills, and experiences are preferred, but not required:
- Master's degree.
Success in This Role
- Within 90 days: data architecture defined, MVP ingestion patterns built, data catalog prototype created.
- Within 6 months: unified data layer operational with initial analytics and compliance datasets.
- Within 12 months: data platform supporting both product functionality and cross-organizational analytics — becoming the single source of truth for the company.
Why Consider Joining FIS now?
- High-Growth Trajectory: Poised for accelerated expansion with private equity backing.
- Empowered Leadership Role: Opportunity to drive tangible impact across the business.
- Mission-Driven Work: Tell a compelling story that protects consumers and financial institutions alike.
The following behaviors are required:
- Strategic Thinking: Anticipates long-term business and technical needs when designing data systems, ensuring solutions remain scalable, secure, and adaptable.
- Technical Excellence: Demonstrates deep technical proficiency by consistently delivering high-quality, efficient, and maintainable data architectures and pipelines.
- Collaboration: Builds strong partnerships across product, engineering, and business teams to translate complex requirements into effective data solutions.
- Communication: Clearly conveys complex data concepts in simple, actionable terms to ensure understanding across technical and non-technical audiences.
- Accountability: Takes ownership of outcomes, ensuring deliverables meet standards for reliability, performance, and compliance.
- Data Stewardship: Upholds data integrity, security, and governance principles, recognizing the organization’s data as a critical enterprise asset.
- Adaptability: Responds effectively to changing priorities, technologies, and business needs while maintaining focus on delivering value.
- Continuous Improvement: Actively identifies opportunities to optimize data processes, enhance performance, and reduce operational costs.
- Mentorship: Supports and develops teammates by sharing knowledge, promoting best practices, and fostering technical growth.
- Customer Focus: Designs data solutions with the end user in mind, ensuring accessibility, reliability, and trustworthiness of information delivered.
F&I Sentinel is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status, or other characteristics protected by law.