AWS Data Engineer

Overview

We are looking for an experienced AWS Data Engineer to design and implement data lake architectures and analytics solutions on cloud platforms. You will help shape best practices and provide expert guidance on data engineering projects, contributing to the evolution of our data and analytics capabilities.

Key Responsibilities

• Design and implement reference and solution architectures for group and corporate data lakes and workflows on AWS, with optional use of Google Cloud.
• Develop user experiences for analytics solutions tailored to business and user needs.
• Define data engineering and analytics best practices in collaboration with architects.
• Act as a consultant, subject matter expert, and lead on data engineering and analytics projects.
• Contribute to updating the vision, mission, and operating model of the Data and Analytics function.

Requirements

• Minimum 5 years of progressive experience as an AWS Data Engineer with full-cycle AWS data lake implementation.
• Experience with Google Cloud Platform and BigQuery preferred.
• Functional knowledge in Finance, Procurement, HR, Logistics, or Communications.
• Experience managing projects using agile methodologies with a product focus.
• Expert knowledge of AWS data lake services including Redshift, S3, Glue, Athena, DynamoDB, and Lambda.
• Hands-on experience with data parsing, cleansing, quality definitions, pipelining, storage, and ETL scripting.
• Proficiency in Python, PySpark, and SQL.
• Experience consuming REST APIs with various authentication methods within an AWS Lambda architecture.
• Ability to orchestrate, debug, and schedule batch jobs using AWS Glue and Lambda.
• Understanding of AWS security features such as IAM roles and policies.
• Exposure to DevOps tools.
• AWS certification is highly preferred.

Nice to Have

• Knowledge of the construction and building materials industry.
• SAP BW and BusinessObjects development experience.