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Senior Engineer - Data Analyst

Eaton
Maharashtra, IND
Onsite
Discovered 3 weeks ago
Data analyticsProcess automationSolution architectureDatabase managementData transformation and quality assuranceBusiness intelligence tools

Full Job Posting

Role overview

The EIIC functional excellence organization supports Eaton engineering process transformation and deploys standardized processes across sectors and businesses.

The Senior Engineer - Data Analyst and Automation Engineer role uses big data analytics and automation to solve critical problems and improve processes.

Responsibilities

  • Gather and prioritize customer needs, translate them into requirements, and communicate insights for data-driven decisions.
  • Define end-to-end automation and solution architecture; select suitable languages, tools, and frameworks; establish coding standards and practices.
  • Aggregate data from varied sources, apply suitable analytics algorithms, and recommend actions based on insights.
  • Produce dashboards and reports for KPIs, targets, historical trends, and customer data needs; identify new uses for data.
  • Manage multiple projects and deliver quality work on time while advancing project management standards and dashboard reporting.

Qualifications

  • Bachelor's degree in Computer, Electrical, Mechanical, or Electronics Engineering and 6–9 years of experience.
  • Strong understanding of organizational processes.

Technical skills

  • Experience in database management, data solutions, transformation, and data quality assurance; one or more BI tools.
  • Experience with batch ETL/ELT and on-demand API or SQL integration; basic knowledge of third normal form, star, or snowflake data modeling.
  • Dashboard and KPI reporting experience; visualization using one or more of Power BI, Grafana, R, or Python.
  • Experience developing and supporting data pipelines, including code, orchestration, and quality; basic DevSecOps and CI/CD knowledge.
  • Engineering and program management data knowledge, including SAP or Oracle datasets, is recommended.

Work approach

  • The description emphasizes process management, problem solving, decision quality, results orientation, critical thinking, communication, and interpersonal skills.

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