Senior Data Engineer

Senior Data EngineerWe are seeking a Senior Data Engineer to design and build the cloud data foundation supporting our key platforms. This role will develop the pipelines, storage architecture, data models, APIs, and quality controls required to make large volumes of operational, engineering, analytical, and contextual information securely and reliably available to applications and AI capabilities. The ideal candidate combines modern AWS data engineering expertise with a strong understanding of data quality, time-series information, and scalable data architectures.Key ResponsibilitiesDesign and implement the cloud data architecture.Build scalable ingestion, transformation, storage, and serving pipelines on AWS.Develop pipelines for operational, historical, engineering, application, and contextual data.Design data models optimized for analytical applications and AI consumption.Establish appropriate storage patterns across relational, object, time-series, and analytical data stores.Develop APIs and services enabling tools and agents to retrieve data consistently.Establish automated data-quality validation, reconciliation, and monitoring.Implement metadata management, lineage, cataloging, and data-governance practices.Design appropriate mechanisms for data segregation and access control.Optimize data pipelines for scalability, performance, reliability, and cost.Partner with operational subject-matter experts to validate the meaning and quality of source data.Support migration of relevant information from document-based repositories into structured cloud-hosted data services.Collaborate with AI/ML engineers to create reliable datasets, feature pipelines, retrieval mechanisms, and knowledge sources.Establish reusable data integration patterns that accelerate onboarding of additional use cases and sites.Required QualificationsEducation: Bachelor's degree in Computer Science, Data Engineering, Engineering, or a related field.Experience: 5+ years of data engineering experience.Technical Skills:Strong Python and SQL skills.Hands-on experience building production data pipelines in AWS.Experience with AWS data technologies such as S3, Glue, Lambda, RDS/Aurora, Redshift, Athena, Kinesis, or equivalent technologies.Experience with ETL/ELT architecture and orchestration frameworks.Strong knowledge of relational and non-relational database design.Experience implementing automated data-quality processes.Experience building APIs or data services.Understanding of data governance, lineage, security, and access-control principles.Preferred QualificationsExperience with time-series data.Experience with streaming/event-driven architectures.Experience with industrial IoT, SCADA, historians, or operational technology data.Experience with energy-generation assets such as solar, battery storage, wind, or conventional generation.Experience designing data architectures supporting AI/ML and generative AI applications.Experience with vector databases and retrieval architectures.Experience working with high-volume telemetry datasets.