Establish and document the organization’s first comprehensive data topology and inventory , transforming undocumented legacy flows into a structured, scalable platform blueprint.
Architect cross-application data models and Data Contracts (OpenAPI/AsyncAPI) to standardize identity layers and ensure consistency across the product lifecycle.
Design high-performance data flows and transformation layers that surface usage analytics and recurring revenue signals to drive AI-powered insight generation.
Lead the integration of platform service layers with mobile/web applications to streamline device commissioning and cross-functional data access.
Replace ad-hoc processes with robust workflow orchestration (e.g., Airflow, dbt) and CI/CD pipelines to ensure 99.9% data reliability and "Data-as-Code" standards.
Drive the technical proposal process, conducting cost-benefit analyses for new systems to balance immediate delivery with long-term platform health.
Implement automated data quality monitoring, lineage tracking, and observability practices to ensure high-fidelity data for downstream analytics and compliance.
Engineer data lifecycle policies that strictly adhere to global privacy regulations (GDPR/CCPA) and enterprise security standards.
Establish and enforce rigorous coding standards and peer review processes, mentoring the team to transition from "plumbing" to modern DataOps practices.

Requirements

Bachelor’s Degree in Computer Science, Data Science, Software Engineering, or a related quantitative field.
Master’s Degree in a technical field preferred.
7+ Years in Data Engineering: With at least 2+ years in a Lead or Staff capacity , specifically owning the technical roadmap.
Ground-to-Cloud" Experience: A proven track record of entering environments with high technical debt/minimal documentation and successfully implementing a formal data strategy and topology.
Stakeholder Management: Experience working directly with Product and Executive teams to translate business questions into technical data requirements.
AI/ML Integration: Previous experience building feature stores or pipelines specifically designed to feed AI/ML models or LLMs.

Benefits

Health, dental and vision insurance coverage, helping you “be safe, be healthy”.
A commitment to your future with a 401K plan, offering a 6% company match and no vesting period
Tuition Reimbursement
Unlimited PTO
Employee Discounts through Perks at Work
Community involvement and opportunities to give back so you can “serve others, not yourself”
Opportunities to leverage your unique strengths through CliftonStrengths testing and coaching

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data topologydata modelsData ContractsOpenAPIAsyncAPIdata flowsworkflow orchestrationAirflowdbtdata quality monitoring

Soft Skills

leadershipstakeholder managementmentoringcommunication

Certifications

Bachelor’s Degree in Computer ScienceBachelor’s Degree in Data ScienceBachelor’s Degree in Software EngineeringMaster’s Degree in a technical field