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Cloud Engineer- Azure Data Services

Work from home Full-time role Hiring

Job Description

Position Title: Data Engineer Company Name: top utility company in Evansville ,IN or Houston, TX CenterPoint Location: Hybrid (4x onsite and 1 remote)

  • Evansville IN 47708

$60-62/hr C2C Need LinkedIn USC or GC Can now be open to Houston, TX. Either relocate or already local. Still we need to be able to convert full time Project Details: Looking for a Data Engineer that will work in the IT and Data Analytics group at CenterPoint. They will help with developing, constructing, test and maintain data acquisition pipelines for large volumes of data. This includes batch and real time processing. They will build help with building large datasets, and collaborate with stakeholders to identify opportunities for data acquisition. Looking for someone who can facilitate the overarching data process from python all the way through to SQL. Must Have Skills: Level 2:

  • Bachelor's degree in Data Science, Analytics, Mathematics, Statistics, Computer Science or STEM
  • Minimum of 2 years' experience of related experience in data engineering, data analysis, ETL or similar role delivering data pipelines
  • Must have experience with Python and Strong Proficiency in SQL with direct working experience leveraging this skill
  • Understanding in data modeling concepts and experience with data modeling tools
  • Bachelor's degree in Data Science, Analytics, Mathematics, Statistics, Computer Science or related field

Level 3

  • Minimum of 5 years' experience of related experience in data engineering, data analysis, ETL or similar role delivering data pipelines
  • Experience with Google Big Query, Python and Strong Proficiency in SQL with direct working experience leveraging this skill
  • Understanding in data modeling concepts and experience with data modeling tools
  • GCP experience

Soft Skills:

  • Excellent facilitation, communication, and interpersonal skills
  • Excellent problem-solving and analytical skills with diligence
  • Experience interacting with employees of all levels to present technical data in a non technical manner
  • Ability to translate complex data concepts into understandable insights for non technical stakeholders

Nice to have Skills:

  • Utility experience
  • Experience with data governance
  • Experience working in an agile team environment

Education/certification requirements:

  • Bachelor's degree in Data Science, Analytics, Mathematics, Statistics, Computer Science or related field

Day to Day responsibilities:

  • Develop, construct, test and maintain data acquisition pipelines for large volumes of structed and unstructured data. This includes batch and real-time processing.
  • Build large and complex datasets based on business requirements.
  • Construct 'big data' pipeline architecture
  • Identifies opportunities for data acquisition via collaborating with stakeholders and business clients.
  • Leverages a variety of tools such as Python, SAP Data Services, Dataflow, DataStream, Google Cloud Functions, Spark, Google Cloud Run, SAP SLT, Google Pub Sub, etc. to integrate systems and data pipelines.
  • Recommends ways to improve data quality, reliability, and efficiency.
  • Develop JSON messaging structure for integrating with various applications.
  • Drive a data engineering strategy focused on delivering data in near real-time using server less technologies.
  • Develop data architecture to optimize performance for dashboards and digital applications.
  • Lead the integration track of various strategic projects.
  • Leverage DevOps and CI/CD practices to ensure the reliability and scalability of data pipelines.
  • Assist in the development and maintenance of data models, data dictionaries, and data documentation to ensure data integrity and consistency.
  • Participate in cross-functional teams to support data-related projects, providing expertise and guidance on data analysis, data management, and data visualization.
  • Stay updated with the latest industry trends and advancements in data analytics, data science, and data engineering, and apply this knowledge to enhance data capabilities within the organization.
  • Constant, initiative-taking pursuit of learning systems, organizational structure, processes, data sets, techniques, etc.
  • Interpret and explain information to audiences who are not familiar with the subject matter, often requiring persuasion.
  • Provide guidance and training to others in the use of modern technologies, theories, concepts, and techniques.
  • Operate with limited supervision, guidance, and direction from leadership and senior staff.

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