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.