Data Engineering Engineer 3//Dearborn, MI//W2 only

Location: 679 - Rotunda Center

Location Address: 17000 Rotunda Drive, DEARBORN, MI, 48120

Position Description

We're seeking a highly skilled and experienced Full Stack Data Engineer to play a pivotal role in the development and maintenance of our Enterprise Data Platform. In this role, you'll be responsible for designing, building, and optimizing scalable data pipelines within our Google Cloud Platform (GCP) environment. You'll work with GCP Native technologies like BigQuery, Dataflow, and Pub/Sub, ensuring data governance, security, and optimal performance. This is a fantastic opportunity to leverage your full-stack expertise, collaborate with talented teams, and establish best practices for data engineering at Ford. Employees in this job function are responsible for designing, building, and maintaining data solutions including data infrastructure, pipelines, etc. for collecting, storing, processing and analyzing large volumes of data efficiently and accurately Key Responsibilities: 1) Collaborate with business and technology stakeholders to understand current and future data requirements 2) Design, build and maintain reliable, efficient and scalable data infrastructure for data collection, storage, transformation, and analysis 3) Plan, design, build and maintain scalable data solutions including data pipelines, data models, and applications for efficient and reliable data workflow 4) Design, implement and maintain existing and future data platforms like data warehouses, data lakes, data lakehouse etc. for structured and unstructured data 5) Design and develop analytical tools, algorithms, and programs to support data engineering activities like writing scripts and automating tasks 6) Ensure optimum performance and identify improvement opportunities

Skills Required

Data/Analytics dashboards

Skills Preferred

GCP

Experience Required

Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Analytics, or a related field (or equivalent combination of education and experience). 5-7 years of experience in Data Engineering or Software Engineering, with at least 2 years of hands-on experience building and deploying cloud-based data platforms (GCP preferred). Strong proficiency in SQL, Java, and Python, with practical experience in designing and deploying cloud-based data pipelines using GCP services like BigQuery, Dataflow, and DataProc. Solid understanding of Service-Oriented Architecture (SOA) and microservices, and their application within a cloud data platform. Experience with relational databases (e.g., PostgreSQL, MySQL), NoSQL databases, and columnar databases (e.g., BigQuery). Knowledge of data governance frameworks, data encryption, and data masking techniques in cloud environments. Familiarity with CI/CD pipelines, Infrastructure as Code (IaC) tools like Terraform and Tekton, and other automation frameworks. Excellent analytical and problem-solving skills, with the ability to troubleshoot complex data platform and microservices issues. Experience in monitoring and optimizing cost and compute resources for processes in GCP technologies (e.g., BigQuery, Dataflow, Cloud Run, DataProc). A passion for data, innovation, and continuous learning.

Education Required

Bachelor's Degree Hybrid Position 4 days a week onsite

Education Preferred

Master's Degree

Additional Safety Training/Licensing/Personal Protection Requirements

Additional Information :

Data Pipeline Architect & Builder: Spearhead the design, development, and maintenance of scalable data ingestion and curation pipelines from diverse sources. Ensure data is standardized, high-quality, and optimized for analytical use. Leverage cutting-edge tools and technologies, including Python, SQL, and DBT/Dataform, to build robust and efficient data pipelines. End-to-End Integration Expert: Utilize your full-stack skills to contribute to seamless end-to-end development, ensuring smooth and reliable data flow from source to insight. GCP Data Solutions Leader: Leverage your deep expertise in GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that not only meet but exceed business needs and expectations. Data Governance & Security Champion: Implement and manage robust data governance policies, access controls, and security best practices, fully utilizing GCP's native security features to protect sensitive data. Data Workflow Orchestrator: Employ Astronomer and Terraform for efficient data workflow management and cloud infrastructure provisioning, championing best practices in Infrastructure as Code (IaC). Performance Optimization Driver: Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions, ensuring optimal resource utilization and cost-effectiveness. Collaborative Innovator: Collaborate effectively with data architects, application architects, service owners, and cross-functional teams to define and promote best practices, design patterns, and frameworks for cloud data engineering. Automation & Reliability Advocate: Proactively automate data platform processes to enhance reliability, improve data quality, minimize manual intervention, and drive operational efficiency.