Expert, Data Platforms Engineer

About the Role

As a Data Engineer in the Data Platforms organization, you will design and deliver advanced data solutions that enable trusted analytics and AI across the enterprise. You will collaborate with stakeholders, solution architects, and global technology teams to build efficient, scalable data flows while upholding strong data‑governance practices, turning raw data into actionable insights for customers and the planet. Key responsibilities include designing and engineering a data lake, developing data pipelines for both structured and unstructured data, and implementing storage, partitioning, semantic layer, and metadata structures to treat data as a product. You will automate governance features such as privacy, security, inventory, and cataloguing, and enhance observability, cost management, and reporting for data‑engineering operations. Additionally, you will build integration testing and quality‑assurance capabilities, evaluate emerging tools, and lead and mentor the Data Delivery teams. • Design and engineer a data lake, including data source identification, extraction, modeling, storage, and governance. • Develop ETL pipelines for structured and unstructured data using warehousing and big‑data tools. • Implement storage patterns, partitioning, semantic layers, and metadata to deliver data as a product. • Automate governance features such as data privacy, security, inventory, and cataloguing. • Build observability, cost‑management, and reporting capabilities for data‑engineering operations. • Create integration testing and quality‑assurance processes aligned with architectural standards. • Evaluate emerging tools and technologies through proof‑of‑concept assessments. • Lead, mentor, and support Data Delivery teams with methodologies and technical knowledge.

Key Responsibilities

• ▸data lake
• ▸etl pipelines
• ▸storage architecture
• ▸data governance
• ▸observability
• ▸team mentoring

What You Bring

The role requires at least six years of technical experience with a focus on data engineering and three or more years of hands‑on experience with AWS services such as S3, Lambda, Glue, and Step Functions. Candidates must be proficient in a programming language (Python, Scala, or Java), have strong SQL skills, knowledge of Spark architecture, and experience with Redshift or Athena. Additional required skills include Terraform, Git, CI/CD pipelines, AWS Glue/Lake Formation, and data‑governance tools. Schneider Electric does not sponsor visas; candidates must be authorized to work in the United States without future visa assistance. This full‑time internal role is limited to on‑site candidates in Nashville, TN or Louisville, KY, and consultants or contractors will not be considered. • Minimum 6 years technical experience with a focus on data engineering; 3 years hands‑on AWS (S3, Lambda, Glue, Step Functions, etc.). • Proficiency in Python, Scala, or Java; strong SQL and Spark performance‑tuning skills. • Experience with Redshift, Athena, or similar distributed compute engines. • Skilled in Terraform, Git, CI/CD pipelines (e.g., Jenkins), and AWS Glue/Lake Formation for data governance. • Authorized to work in the U.S. without visa sponsorship; on‑site location limited to Nashville, TN or Louisville, KY.

Requirements

• ▸aws
• ▸python
• ▸sql
• ▸spark
• ▸terraform
• ▸us authorization

Benefits

The position is U.S.-based with a total compensation range of $114,400 to $171,600 per year, including base salary and short‑term incentive. Pay is determined by performance, skills, experience, and education within the range. Schneider Electric also provides a comprehensive benefits package that includes medical, dental, vision, life insurance, Benefit Bucks, flexible work arrangements, paid family leave, 401(k) with match, well‑being programs, 12 holidays, 15 days PTO (pro‑rated), stock purchase eligibility, and military leave benefits.

Work Environment

Hybrid