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Data Engineer

4 months ago

Salt Lake City, United States ConsultNet Technology Services and Solutions Full time

Data Engineer (NO C2C PLEASE)

Salt Lake City, UT

Long-Term Contract: $50-$75 per hour


Our client is in search of a Data Engineer to join their team on a long-term contract. The ideal candidate for this position has experience in Azure, data pipelines, data architecture and warehousing, and has dabbled in machine learning. They are a Data Engineer with a passion for data, and for making peoples' lives easier. They enjoy both philosophical discussions and physical deployments and are comfortable working with multiple teams.


Principal Duties

  • Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity.
  • Designs efficient data structures and database schemas, as well as working with distributed system architecture and non-relational databases.
  • Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.
  • Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
  • Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
  • Works closely with a team of engineers, product managers, and analysts.
  • Defines company data assets (data models), jobs to populate data models.
  • Designs data integrations and data quality framework.
  • Designs and evaluates open source and vendor tools for data lineage.
  • Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.
  • Other duties as assigned.


Requirements:

  • Degree – Candidate must possess a bachelor's degree from an accredited college in Computer Science, Information Technology, Business, or equivalent experience.
  • Functional Experience – Candidates must have 5+ years of experience with BI reporting tools like Power BI or Tableau.
  • Functional Experience – Candidates must have 3+ years of experience with large sets of regulated data, designing efficient data structures, and database schemas, as well as working with distributed systems architecture and CosmosDB.
  • Functional Experience – Candidates must have 3+ years of experience with SQL and Python, with a focus on building reusable frameworks.
  • Functional Experience – Candidates must have 3+ years' experience with integration technologies and protocols such as SOAP, REST, JSON and APIs, with experience in handling streaming data.
  • Functional Experience - Data Lake and/or Date Warehousing – Experience with planning and implementing a data warehouse, data lake, or other data repositories is required.
  • Functional Experience - Hands-on experience in Azure Data Factory, DataBricks, Azure Storage, SQL Pools, CI/CD Pipeline Design along with other Azure services like functions and Logic apps.
  • Interpersonal Relationships – Candidates must demonstrate the ability to work well with others of all personality types while demonstrating problem-solving and the ability to prioritize tasks.
  • Communication – Candidates must demonstrate the ability to communicate in verbal and written form with both technical and non-technical personnel.
  • Initiative – Candidates must demonstrate success as a self-starting, hardworking and inquisitive worker.
  • Teamwork – Candidates must demonstrate the ability to work with cross-functional teams to deliver on a common goal.
  • Agile/Scrum - Candidates must demonstrate experience in an agile product environment to include deep understanding and experience with agile methodologies.


Bonus skills:

  • Certifications: Azure Data Engineering, Azure DBA, Azure Developer or others related to the position
  • Domain Driven Design – Understanding and experience with Domain Driven Design
  • Financial or Education Domains and their data standards – Ed-Fi, CEDS, SIF, GAAP, etc.
  • Knowledge and Experience with Data Privacy, Data Governance, and Data Cataloguing principles.
  • Machine Learning – Knowledge of best practices and experience with an LLM.