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Schneider Electric

Global energy management and automation provider

Expert Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeMonterrey, Nuevo Leon, MexicoNo salary listedIn-person

About the Job

Requirements

  • At least 6 years of experience in technical roles focused on data engineering.
  • At least 3 years of hands-on experience with AWS services, including S3, KMS, Lambda, Glue or Spark, SQS, EventBridge, and AWS Step Functions.
  • At least 3 years of hands-on experience writing clean, modular, testable, and maintainable code using functional or object-oriented principles.
  • Understanding of AWS networking concepts, including VPCs, subnets, routing, NAT gateways, and security groups.
  • Proficiency in IAM concepts, including roles, policies, assume-role, and cross-account access.
  • Experience with at least one programming language, such as Python, Scala, or Java.
  • Understanding of Spark architecture, execution plans, and performance tuning.
  • Strong SQL skills, including complex joins, window functions, and aggregations, and experience with Redshift, Athena, or another distributed compute engine.
  • Experience writing and maintaining Terraform scripts.
  • Familiarity with Git, GitHub workflows, and CI/CD tools such as Jenkins.
  • Hands-on experience with data governance, cataloguing, and discovery tools such as AWS Glue and Lake Formation.
  • Exposure to data lake architectures and data governance practices.
  • Familiarity with monitoring and logging implementation.
  • Advanced cloud and on-premises knowledge of NoSQL database structures, including AWS DynamoDB and MongoDB.
  • Knowledge of data management, integration, and data quality tools spanning no-code, low-code, and code-first methodologies.

Responsibilities

  • Design, develop, and engineer data lakes through data source identification, data extraction, data modelling, data store design, and governance.
  • Develop data flows to ingest and transform structured and unstructured data using warehousing and big data methodologies and tools, building refined and aggregated data assets for business intelligence and AI enablement.
  • Implement efficient patterns for data storage, partitioning, semantic layers, and metadata structures to enable consumption of data as a product.
  • Implement automation capabilities for data privacy and protection, data inventory and cataloguing, authorization, and data security governance features.
  • Implement enhanced observability, cost management, and reporting strategies for data engineering operations.
  • Build integration testing and quality assurance capabilities while ensuring compliance with architectural standards for development.
  • Assess the latest tools and technologies through proofs of concept to develop solutions and help evolve the technology landscape.
  • Lead, mentor, and support Data Delivery teams with methodologies, tools, and technical knowledge.

About the Company

Schneider Electric

Global energy management and automation provider

Schneider Electric is a global specialist in energy management and automation. It helps homes, businesses, and industries run electricity more efficiently by selling electrical products, automation hardware, software, and related services. Its offerings cover electrification, automation, and digitization, and solutions connect devices, collect data, and control systems to optimize energy use in smart industries, resilient infrastructure, and data centers. The company distinguishes itself with a broad, end-to-end portfolio and a worldwide presence in over 100 countries, combining hardware, software, and services to address sustainability and reliability. Its goal is to help people and organizations use energy more efficiently, reduce environmental impact, and improve uptime and reliability.

Company size
10,001+
Company stage
IPO
Headquarters
Rueil-Malmaison, France
Founded
1836

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