Data Engineer – Full Stack

This is a fully remote position, open to applicants in Ohio.

📋 Description

• Create and execute comprehensive data pipelines (ETL/ELT) that gather, process, and organize large-scale enterprise data, which includes telemetry/vehicle data as well as various structured and unstructured sources.

• Develop and sustain Generative AI pipelines — encompassing embedding generation, vector store indexing, retrieval-augmented generation (RAG), and LLM orchestration — to facilitate intelligent search, summarization, and conversational analytics on enterprise data.

• Transition and modernize data assets to a centralized data platform (e.g., BigQuery) utilizing established data lake/warehouse architectures (Bronze/Silver/Gold or Medallion architecture) to support analytics, reporting, and AI/ML operations.

• Design scalable data models and data warehouses, focusing on optimizing query performance, maintainability, cost-effectiveness, and downstream AI utilization.

• Construct and manage robust orchestration pipelines using Airflow/Astronomer or Schedule Query, implementing secure, reproducible CI/CD workflows (Terraform + Git) for both data and AI artifacts.

• Integrate LLM APIs and AI services (e.g., Vertex AI, OpenAI, LangChain) into data workflows to automate processes such as data enrichment, classification, anomaly narratives, and natural-language interfaces.

• Develop and maintain dependable data and model quality checks, lineage, and monitoring utilizing observability tools (e.g., Splunk, Looker/Grafana/Tableau/Power BI dashboards) to quickly identify and resolve issues in data and AI pipelines.

• Enforce data governance, security, and compliance measures (data lineage, access controls, PII/PHI protection, prompt injection safeguards, responsible AI guidelines) in collaboration with security and privacy teams.

• Spearhead the design and delivery of analytics-ready and AI-ready data assets for cross-functional teams, including dashboards, alerts, self-service analytics, and AI-powered insight tools.

• Assess, prototype, and bring to production emerging Generative AI capabilities (agents, function calling, fine-tuning, multimodal models) to address business challenges and enhance platform intelligence.

• Guide and mentor junior engineers in data engineering, AI/ML integration patterns, prompt engineering best practices, and documentation standards.

• Work alongside data scientists, ML engineers, product managers, and business stakeholders to convert requirements into scalable data and AI solutions and timely insights.

• Oversee cost and capacity planning for cloud and AI resources; optimize storage, compute, and token usage across GCP services (BigQuery, Dataflow, Dataproc, GCS, Vertex AI).

• Engage in on-call rotations and incident response to ensure the high availability of data and AI services.

⛳️ Requirements

• A bachelor’s degree.

• Over 5 years of experience in data engineering, data platforms, or a related field.

• More than 3 years of practical experience with Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Dataproc; Schedule Query or equivalent scheduling/orchestration) or AWS.

• At least 1 year of experience working with Generative AI technologies — including LLMs, embeddings, vector databases, RAG architectures, or AI orchestration frameworks (e.g., LangChain, Semantic Kernel, LlamaIndex).

• A minimum of 1 year of experience developing a Semantic Data layer to support AI agents.

• Hands-on experience in constructing and managing data pipelines with orchestration tools (Airflow/Astronomer; Schedule Query).

• Familiarity with infrastructure-as-code and CI/CD (Terraform, Git, and related tools).

• Proven capability to design and implement analytics-ready data assets and dashboards; experience with BI tools (Looker, Tableau, Power BI, Grafana) for monitoring and reporting.

• Excellent communication skills and the ability to work efficiently with cross-functional teams (engineering, analytics, product, security).

🏝️ Benefits

• Immediate medical, dental, vision, and prescription drug coverage.

• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care, and more.

• Family building benefits including reimbursement for adoption and surrogacy expenses, fertility treatments, and additional support.

• Vehicle discount program available for employees and their family members, along with management leases.

• Tuition assistance to support further education.

• Established and active employee resource groups fostering community engagement.

• Paid time off for individual and team community service initiatives.

• A generous schedule of paid holidays, including the week between Christmas and New Year's Day.

• Paid time off with the option to purchase additional vacation days.