Expert, Data Platform Engineer

Join Schneider Electric and help us power a sustainable future through data. As a Data Engineer within our Data Platforms organization, you will play a critical role specifically within our Data Distribution Center. This team is responsible for making enterprise analytics data securely discoverable, scalable, governed, and performant for consumption across the business, including BI and AI use cases.

What You Will Do

• Design, build, and operate scalable and secure analytical data platforms with a strong focus on AWS Redshift.
• Architect Redshift environments (serverless and provisioned), including decisions around cost, scalability, performance, and workload patterns.
• Optimize Redshift performance through query tuning, distribution styles, sort keys, workload management, and capacity planning.
• Implement monitoring and observability using AWS CloudWatch and related tooling to proactively manage performance and reliability.
• Enable governed data access through data cataloging, role-based access, audits, and security controls.
• Work closely with data processing, ingestion, and architecture teams to support the medallion (bronze/silver/gold) architecture, with emphasis on the gold layer.
• Apply data governance practices using AWS Lake Formation, IAM, and related services.
• Develop and maintain Python-based automation and infrastructure-as-code (Terraform) to support platform operations.
• Support ongoing operations of the Data Distribution Center, ensuring stability of analytics services for downstream teams.
• Evaluate and evolve platform capabilities while balancing legacy tooling with future-state architecture.

Required Qualifications

• 6+ years of experience in data engineering, analytics engineering, or platform engineering roles.
• Strong hands-on experience with AWS Redshift, including architecture, scaling, monitoring, and performance optimization.
• Advanced SQL skills (complex joins, window functions, performance tuning).
• Solid experience with Python for data workloads, automation, or platform tooling.
• Deep familiarity with AWS core services (S3, IAM, CloudWatch, KMS, networking concepts such as VPCs and security groups).
• Experience implementing data governance, security, and access controls using tools such as AWS Lake Formation and IAM.
• Understanding of cloud cost management, scalability tradeoffs, and operational best practices.

Nice to Have

• Experience with alternative analytics platforms such as Snowflake, Databricks, or Oracle, with ability to translate those concepts to AWS Redshift.
• Exposure to legacy ETL tools (e.g., Informatica).
• Experience supporting BI tools such as Tableau or Power BI.
• Familiarity with CI/CD pipelines, GitHub workflows, and Jenkins.
• Prior experience working in a lakehouse or medallion architecture.