Schneider Electric

Software Engineer - Analytics

Schneider Electric • $117K — $176K *
Andover, MA 01810In-Person
Enterprise Technology
Less than 5 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Bachelor's degree with 5+ years or Master's degree with 3+ years of experience in Software Engineering, Analytics Engineering, Data Engineering, or related fields.
  • Strong Python skills including design patterns, testing, packaging, logging, and API integration.
  • Hands-on experience in building, deploying, and supporting production analytics solutions.
  • Familiarity with time-series data and data from industrial, IoT, or operational technology sources.
  • Experience with CI/CD workflows and cloud-native deployment architectures.

Responsibilities

  • Design, build, and maintain end-to-end analytics pipelines.
  • Write production-quality Python code adhering to modern software engineering practices.
  • Design deployment architectures compatible with Databricks, Azure, and containers.
  • Implement orchestration patterns for data handling and error management.
  • Develop resilient analytics capable of managing real-world data challenges.
  • Establish monitoring and observability for analytics applications and services.
  • Collaborate with cross-functional teams to deliver scalable solutions.

Benefits

  • Impactful involvement in innovative AI projects that influence business strategy.
  • Supportive and collaborative team culture for professional growth.
  • Opportunities to expand expertise and stay updated in AI technology.
  • Autonomy in guiding technical decisions and managing priorities.
Full Job Description
Software Engineer: Advanced Analytics

You will bring together software engineering, analytics, and robust deployment practices to move analytics solutions reliably from prototype to production. This includes building scalable pipelines, deploying and monitoring analytics applications, integrating enterprise systems and services, and ensuring security, governance, and operational reliability.

You have experience building and deploying production analytics solutions and enjoy solving challenges at the intersection of software engineering, industrial data, and cloud platforms. We value strong engineering fundamentals, hands-on deployment experience, and the ability to collaborate with data scientists, domain experts, and business stakeholders.

What you'll be doing
  • Design, build, and maintain end-to-end analytics pipelines from development through deployment and monitoring.
  • Write production-quality Python code using modern software engineering practices, including testing, logging, and error handling.
  • Design deployment architectures that can run across Databricks, Azure, containers, and other cloud environments.
  • Implement orchestration patterns including routing, handoffs, fallback logic, and failure handling.
  • Develop resilient analytics capable of handling real-world data challenges such as missing data, delayed data, communication outages, sensor failures, and inconsistent telemetry.
  • Build and support analytics solutions using time-series data from OT, IoT, and industrial systems.
  • Develop CI/CD pipelines using GitHub Actions, Azure DevOps, or similar technologies.
  • Establish monitoring, observability, and operational support for analytics applications, services, and pipelines.
  • Perform data analysis using SQL to support AI and pipeline development.
  • Develop operational dashboards and visualizations to monitor analytics performance, system health, data quality, and business outcomes.
  • Collaborate with engineering, analytics, product, and business teams to deliver scalable solutions.
  • Apply security, governance, and Responsible AI practices including access controls, auditability, and data protection.

What you bring
  • Background in Software Engineering, Analytics Engineering, Data Engineering, AI Engineering, or a related technical field.
  • Strong Python skills including design patterns, testing, packaging, logging, and API integration.
  • Hands-on experience building, deploying, and supporting production software or analytics solutions.
  • Experience designing and maintaining deployment pipelines, CI/CD workflows, monitoring, and operational support for production systems.
  • Experience working with time-series data and industrial, IoT, or OT data sources.
  • Understanding of common operational data challenges including missing, delayed, noisy, or unreliable sensor data.
  • Knowledge of electrical power systems, energy systems, industrial automation, or related engineering domains.
  • Experience deploying applications using containerized and cloud-native architectures.
  • Experience designing solutions across Databricks, Azure, and similar environments.
  • Experience with GitHub Actions, Azure DevOps, or equivalent CI/CD platforms.
  • Strong SQL (Spark SQL / Delta; relational databases a plus)
  • Familiarity with Power BI, Tableau, or Looker.
  • Bachelor's degree with 5+ years of relevant experience, or Master's degree with 3+ years of relevant experience.

You might also have
  • Experience with Databricks Workflows, Delta Live Tables, or Apache Spark.
  • Experience with Azure Machine Learning, Azure AI Foundry, AKS, or Container Apps.


What's in it for me?
  • High-impact work on innovative AI projects that shape business strategy
  • Collaborative team culture with talented professionals who support your growth
  • Opportunities to expand your expertise and stay at the forefront of AI technology
  • Autonomy to guide technical decisions and set your own priorities

Ready to make your mark in AI? We'd love to hear from you!

About Schneider Electric

Schneider Electric is a multinational corporation that specializes in energy management and automation solutions. The company was founded in 1836 and is headquartered in Rueil-Malmaison, France. Schneider Electric offers a wide range of products and services including electrical distribution, automation and control, and energy management. The company operates in over 100 countries and has a strong presence in the industrial and commercial sectors. Schneider Electric is committed to sustainability and has set ambitious targets to reduce its environmental impact. The company has received numerous awards for its sustainability efforts and is recognized as a leader in the industry.
Learn more about Schneider Electric
Size
166,025 employees
Industry
Manufacturing & Automotive
Founded
1836
NASDAQ
SBGSY
* Ladders Estimates

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