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Data Engineer, IT

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📍 Location: United States

💸 Salary: 100000.0 - 120000.0 USD per year

🔍 Industry: IT

🏢 Company: Adswerve, Inc

🗣️ Languages: English

🪄 Skills: PythonSQLGCPGitJavascriptData engineeringRESTful APIsData visualizationData modeling

Requirements:
  • Extensive experience with Google Cloud Platform (GCP) services, including BigQuery, Dataform, Cloud Storage, Cloud Functions, Cloud Composer, Dataflow, and Pub/Sub
  • In depth understanding of SQL, including the optimization of queries and data transformations
  • Comfortable with Javascript and Python programming languages
  • Excellent communication and collaboration skills
  • Solid understanding of data warehouse, data modeling and data design concepts
  • Experience with ELT processes and data transformation techniques
  • Experience with version control systems (e.g., Git)
  • Strong analytical and problem-solving skills as well as the ability to decompose complex problems
  • Proven track record of managing workloads to consistently meet project deadlines
Responsibilities:
  • Develop scalable and efficient data architectures to support enterprise applications, analytics, and reporting.
  • Design, develop, and maintain efficient and scalable ELT pipelines on the Google Cloud Platform
  • Partner with business stakeholders to understand their business needs and data requirements, and translate those needs into clear, actionable technical solutions that directly address business needs.
  • Create and maintain detailed documentation, including architecture diagrams, standards, and models.
  • Ensure data security, integrity, and availability across the organization.
  • Manage, maintain and develop custom built ELT pipelines for systems unsupported by the organizations integration platform
  • Manage, maintain and optimize the data infrastructure on the Google Cloud Platform
  • Implement and manage data validation and quality check to ensure accuracy, consistency and completeness of data across pipelines.
  • Set up and manage monitoring and alerting for data pipelines and infrastructure to proactively identify failures and performance issues.
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