AWS Data Engineer

Job Description

Must Have Technical/Functional Skills

• Demonstrated experience building platforms and data products

• Demonstrated experience working with data and data warehousing business solutions

• Demonstrated experience with cloud-platform technologies (AWS)

• AWS data engineering services (Glue, Lambda, Redshift), data modeling, and data mesh

• Demonstrated experience with data pipeline tools and Extract, Transform, Load (ETL) services

• Experience configuring Application Programming Interfaces (APIs) for data ingestion

• Experience integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities with data

platforms.

Roles & Responsibilities

• Design and own the end-to-end cloud data platform architecture for Human Resources (HR) data,

including ingestion, 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 and streaming), transformation patterns

(ELT/ETL), and orchestration for HR sources such as HRIS, payroll, Learning Management Systems,

recruiting, time and attendance, benefits, and performance systems

• Design, develop, maintain, and optimize internal company data architecture for complex

databases and data warehouses required to operate the business

• Complete data modeling for acquisition and database implementation in collaboration 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, including data

warehouses and data lakes, with data-access 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 and stability, and operational efficiency of data

and analytics solutions

• Lead the development of repeatable data pipelines across complex multi-cloud 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 source control and CI/CD tooling such as Azure DevOps, GitLab, or Git

Publication-ready job description Page 2

• Experience with cloud platforms and cloud-native technologies

• Experience with cloud technologies and/or cloud-native application development and

microservices.