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, Google Cloud Platform)
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 integrationenvironment.
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 Interfaces (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
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