Data Solutions Architect
14 hours ago
York
Data Solutions Architect – Onsite Position Overview: GM Performance Power Units is seeking a Data Solutions Architect to lead the development of our next-generation data platform, powering advanced analytics and machine learning for high-performance powertrain engineering. This is a senior technical specialist position responsible for architecting, implementing, and optimizing large-scale, cloud-first data infrastructure. Key Responsibilities • Design, architect, and implement scalable data systems integrating on-premises and cloud infrastructure (AWS or Azure)., • Lead development of hybrid data architecture, supporting batch and real-time data analytics across a diverse array of testing data and other large datasets., • Develop robust data pipelines and orchestrate ETL processes using technologies such as Apache Kafka, Apache Airflow, Delta Lake, and Apache Arrow., • Implement and optimize Data Warehousing, Data Lakes, and Lakehouses using SQL, noSQL, and Parquet file formats., • Advance Data Management, Data Orchestration, and Data Architecture best practices to ensure integrity, quality, and accessibility of diverse engineering data sources., • Drive infrastructure automation (Infrastructure as Code) leveraging Terraform and Kubernetes to support dynamic, multi-cloud deployments., • Champion MLOps and CI/CD processes to support continual integration, deployment, and monitoring of machine learning models., • Facilitate machine learning workflows using Databricks, Apache Spark, TensorFlow, and PyTorch, collaborating closely with engineering and data science teams., • Oversee the integration of tools for pipeline monitoring, observability, and real-time reporting, ensuring seamless flow of data for both live and historical analysis., • Provide technical mentorship and leadership to staff, supporting their professional development within a high-performance engineering environment., • Develop, maintain, and enforce architecture standards, best practices, and design patterns., • Ability to bridge business needs with scalable, secure, and cost-effective data and AI solutions., • Bachelor’s in computer science or a related technical field, or equivalent experience., • 8–10+ years of experience in data engineering, systems/cloud engineering, or related fields., • 2–3 years as a data architect or data solutions architect overseeing complex, large-scale data infrastructure., • Deep expertise in AWS or Azure and hybrid architectures (cloud and on-premises)., • Hands-on experience with Python, Apache Spark, Databricks, and Terraform., • Practical knowledge of containers and orchestration with Kubernetes., • Demonstrated ability to design and deploy data lakes, data warehouses, and lakehouse architectures., • Strong background in SQL and noSQL database systems., • Skilled in batch and real-time analytics, data management, ETL, infrastructure as code (IaC), and CI/CD pipelines., • MS in Computer Science or a related technical field., • Deep familiarity with Cloud Technologies and Terraform, including orchestration of codified VPCs, EKS clusters, IAM least-privilege policies, and managing multi-account environments., • Strong experience with workflow and metadata orchestration tools such as Apache Airflow and MLflow.