Cloud Data Engineer

Location: Seattle, WA / Dallas, TX

Job Type: Full-time (Onsite)

Job Description: Must Have Technical/Functional Skills:5+ years of experience building platforms and data products.5+ years of experience working with data and data warehousing business solutions.5+ years of experience with cloud-platform technologies (AWS, Azure, GCP).AWS data engineering services (Glue, Lambda, Redshift), data modeling/Data mesh.5+ years of experience with data pipeline tools and Extract Transform Load (ETL) services. Experience with the configuration of Application Programming Interfaces (APIs) for data ingestion. Experience with Artificial Intelligence (AI) hardware and software integration environment.

Roles & Responsibilities: Design and own the end-to-end cloud data platform architecture for Human Resources (HR) data (ingest, storage, processing, serving, cataloging, and archival).Translate HR analytics and Machine Learning (ML) requirements into logical and physical data models, data products, and platform services. Define and implement data ingestion strategies (batch, streaming), transformation patterns (ELT/ETL), and orchestration for HR sources (HRIS, payroll, Learning Management Systems, recruiting, time and attendance, benefits, performance systems).Design, develop, maintain and optimize internal company data architecture for complex databases/data warehouse required to operate the business. Complete data modelling for acquisition and database implementation collaborating with different stakeholders. Apply data extraction, transformation and loading techniques to connect large and complex data sets from a variety of sources. Lead the creation of data collection frameworks for structured and unstructured data and solve complex data problems to generate features required by data scientists. Lead activities to develop and maintain complex infrastructure systems (e.g., data warehouses, data lakes) including data access Application Programming Interface APIs. Analyze and manage complex data. Guide other data and analytics professionals on data standards and practices. Create a culture of sharing, reuse, design for scale stability, and operational efficiency of data and analytics solutions. Lead build of repeatable data pipelines across complex multi- and hybrid-cloud environments. Leverage automation extensively for scalability, repeatability, and reuse. Generic Managerial Skills, If any: Experience in Human Resources. Experience with DevOps/DevSecOps and CI/CD practices, methodologies and tooling. Experience with Azure DevOps (ADO) or Team Foundation Server (TFS ), GitLab, GIT, IIS, Windows Server. Experience with PCF (Pivotal Cloud Foundry)/Tanzu and/or exposure to Amazon Web Services, Google Cloud Platform, or Microsoft Azure. Experience with Cloud technologies and/or Cloud-native app development and microservices.