Role Description Hello and thank you for your interest! We're looking for folks nationwide who are great at data entry and typing. We offer a flexible work from home remote position that allows you to stay home with the family! The pay range is flexible from $16/ph to $30/ph DOE and level of experience. You'll meet these requirements to work from home remotely: - Stable Internet connection - Work can be done using the following: Phone device, laptop or computer - Must be able to type accurately with a minimum speed of 30 words per minute - Able to focus on tasks without being distracted - Must be resident of the US - Not afraid of emailing clients as needed - Must be 16 years of age or older Data entry clerks come from all different backgrounds including, data entry, telemarketing, customer service, sales, clerical, secretary, administrative assistant, warehouse, inventory, receptionist, call center, part-time, retail fields & more. Qualifications - Must be proficient with basic PC skills - Must have an internet connection - Basic English written language - Basic English spoken language Requirements - Must be able to type accurately with a minimum speed of 30 words per minute - Able to focus on tasks without being distracted - Must be resident of the US - Not afraid of emailing clients as needed Benefits - Flexible work from home remote position - Pay range from $16 to $30 hourly depending on the role, level of experience and proven ability to work from home at the same level as from an office. Company Description Thank you for your interest!

Role Description Ford’s Electric Vehicles, Digital and Design (EVDD) team is charged with delivering the company’s vision of a fully electric transportation future. EVDD is customer-obsessed, entrepreneurial, and data-driven and is dedicated to delivering industry-leading customer experience for electric vehicle buyers and owners. You’ll join an agile team of doers pioneering our EV future by working collaboratively, staying focused on only what matters, and delivering excellence day in and day out. Join us to make positive change by helping build a better world where every person is free to move and pursue their dreams. In this role... - Architect and scale end-to-end data and AI pipelines on GCP, transforming complex telemetry and enterprise data into high-quality, analytics-ready assets using Medallion architectures. - Design and integrate Gen AI capabilities — including LLM-powered data enrichment, retrieval-augmented generation (RAG), and intelligent automation — into the data platform. - Lead the implementation of robust CI/CD workflows, rigorous data governance, and security controls while mentoring junior talent and driving engineering best practices. - Collaborate with cross-functional stakeholders and optimize cloud performance to ensure the data and AI platform remains secure, cost-effective, and highly available. What you'll do... - Design and implement end-to-end data pipelines (ETL/ELT) that ingest, process, and curate large-scale enterprise data, including telemetry/vehicle data and other structured/unstructured sources. - Build and maintain Gen AI pipelines — including embedding generation, vector store indexing, retrieval-augmented generation (RAG), and LLM orchestration. - Migrate and modernize data assets to a centralized data platform (e.g., BigQuery) using principled data lake/warehouse architectures (Bronze/Silver/Gold or Medallion architecture). - Architect scalable data models and data warehouses, optimizing for query performance, maintainability, cost efficiency, and downstream AI consumption. - Develop and operate robust orchestration pipelines using Airflow/Astronomer or Schedule Query, with secure, reproducible CI/CD workflows (Terraform + Git). - Integrate LLM APIs and AI services (e.g., Vertex AI, OpenAI, LangChain) into data workflows to automate data enrichment, classification, anomaly narratives, and natural-language interfaces. - Build and maintain reliable data and model quality checks, lineage, and monitoring with observability tools (e.g., Splunk, Looker/Grafana/Tableau/Power BI dashboards). - Implement data governance, security, and compliance controls in collaboration with security and privacy teams. - Lead the design and delivery of analytics-ready and AI-ready data assets for cross-functional teams. - Evaluate, prototype, and productionize emerging Gen AI capabilities to solve business problems and improve platform intelligence. - Mentor and coach junior engineers on data engineering, AI/ML integration patterns, prompt engineering best practices, and documentation standards. - Collaborate with data scientists, ML engineers, product managers, and business stakeholders to translate requirements into scalable data and AI solutions. - Monitor cost and capacity planning for cloud and AI resources; optimize storage, compute, and token usage across GCP services. - Participate in on-call rotations and incident response to maintain high availability of data and AI services. Qualifications - A bachelor's degree - 5+ years of experience in data engineering, data platforms, or a similar role. - 3+ years of hands-on experience with Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Dataproc; Schedule Query or equivalent scheduling/orchestration) or AWS. - 1+ years of experience working with Generative AI technologies — including LLMs, embeddings, vector databases, RAG architectures, or AI orchestration frameworks. - 1+ year experience building Semantic Data layer to serve AI agents. Requirements - Practical experience building and operating data pipelines with orchestration tools (Airflow/Astronomer; Schedule Query). - Experience with infrastructure-as-code and CI/CD (Terraform, Git, and related tooling). - Demonstrated ability to design and implement analytics-ready data assets and dashboards; familiarity with BI tools (Looker, Tableau, Power BI, Grafana). - Strong communication skills and ability to work effectively 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 adoption and surrogacy expense reimbursement, fertility treatments, and more - Vehicle discount program for employees and family members and management leases - Tuition assistance - Established and active employee resource groups - Paid time off for individual and team community service - A generous schedule of paid holidays, including the week between Christmas and New Year’s Day - Paid time off and the option to purchase additional vacation time.

• Design and implement end-to-end data pipelines (ETL/ELT) that ingest, process, and curate large-scale enterprise data, including telemetry/vehicle data and other structured/unstructured sources. • Build and maintain Gen AI pipelines — including embedding generation, vector store indexing, retrieval-augmented generation (RAG), and LLM orchestration — to enable intelligent search, summarization, and conversational analytics over enterprise data. • Migrate and modernize data assets to a centralized data platform (e.g., BigQuery) using principled data lake/warehouse architectures (Bronze/Silver/Gold or Medallion architecture) to power analytics, reporting, and AI/ML workloads. • Architect scalable data models and data warehouses, optimizing for query performance, maintainability, cost efficiency, and downstream AI consumption. • Develop and operate robust orchestration pipelines using Airflow/Astronomer or Schedule Query, with 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 data enrichment, classification, anomaly narratives, and natural-language interfaces. • Build and maintain reliable data and model quality checks, lineage, and monitoring with observability tools (e.g., Splunk, Looker/Grafana/Tableau/Power BI dashboards) to rapidly detect and resolve data and AI pipeline issues. • Implement data governance, security, and compliance controls (data lineage, access controls, PII/PHI protection, prompt injection safeguards, responsible AI guardrails) in collaboration with security and privacy teams. • Lead 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. • Evaluate, prototype, and productionize emerging Gen AI capabilities (agents, function calling, fine-tuning, multimodal models) to solve business problems and improve platform intelligence. • Mentor and coach junior engineers on data engineering, AI/ML integration patterns, prompt engineering best practices, and documentation standards. • Collaborate with data scientists, ML engineers, product managers, and business stakeholders to translate requirements into scalable data and AI solutions and timely insights. • Monitor cost and capacity planning for cloud and AI resources; optimize storage, compute, and token usage across GCP services (BigQuery, Dataflow, Dataproc, GCS, Vertex AI). • Participate in on-call rotations and incident response to maintain high availability of data and AI services.

Role Description We’re looking for a Data Engineer to join our Data Systems team and help build the modern data foundation behind our business. This role is all about turning complex data into scalable, reliable solutions that power reporting, analytics, integrations, and AI-driven insights across the company. You’ll design and support cloud-native data platforms using Microsoft’s modern data ecosystem, while helping modernize legacy systems and shape the future of our data environment. We’re looking for someone who enjoys solving problems, building scalable systems, and partnering across teams to turn ideas into action. Qualifications - 3-5+ years of overall IT experience, including 3+ years focused on data engineering - Strong experience with Microsoft SQL Server, T-SQL, stored procedures, views, and SSIS - Hands-on experience with Microsoft Azure and Microsoft Fabric - Experience with Azure Data Factory, Azure Data Lake Storage Gen2, Azure SQL, and Logic Apps - Familiarity with Medallion Architecture (Bronze/Silver/Gold) data modeling approaches - Experience with Power BI reporting and dashboard development preferred - Exposure to data science workflows, machine learning, or AI deployments is a plus - Strong analytical and problem-solving skills - Ability to communicate technical concepts clearly to both technical and non-technical audiences - A collaborative mindset with the ability to work independently and cross-functionally Requirements - Design, develop, and optimize database objects including tables, views, and stored procedures within Microsoft Fabric - Build and maintain scalable ETL/ELT pipelines using Microsoft Fabric Pipelines, Azure Data Factory, SSIS, and Azure Data Lake Storage Gen2 - Modernize and migrate legacy SSIS solutions into cloud-native Azure and Fabric environments - Partner with engineers, analysts, and business teams to develop scalable data warehouse and lakehouse solutions - Integrate data from internal and third-party systems using APIs, FTP/SFTP, and cloud ingestion patterns - Monitor and support production data pipelines to ensure reliability, performance, and data quality - Contribute to data architecture best practices around governance, security, scalability, and optimization - Help support a modern analytics environment that enables enterprise reporting, advanced analytics, and AI-driven insights Benefits - Flexibility: Work that fits your life – with a remote schedule, unlimited vacation, 9 sick days, 10 company holidays, and 2 paid volunteer days. - Great Benefits: Comprehensive healthcare plans, a 401(k) with company match and immediate vesting, paid parental leave, disability coverage, life insurance, and more. - Great People: A casual, high-energy environment where authenticity is celebrated, curiosity is welcomed, and creativity is supported.