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Data Engineer

Summary

Builds and maintains cloud-based data pipelines, warehouses, and dashboards using SQL, Python, and tools like BigQuery or Redshift.

Requirements:

  1. Experience: Proven experience as a Data Engineer or similar role with a focus on data pipelines, cloud infrastructure, and reporting.
  2. Technical Skills: Strong understanding of data engineering concepts, tools, and technologies (e.g., SQL, Python, ETL tools, cloud platforms).
  3. Cloud Platforms: Experience with major cloud platforms (e.g., AWS, Azure, GCP) and their data-related services (e.g., data warehouses such as BigQuery/Redshift, data lakes, data pipelines).
  4. Data Modeling: Proficiency in data modeling techniques (e.g., dimensional, normalized) and data warehouse design.
  5. Reporting and Visualization: Expertise in using reporting and visualization tools (e.g., Looker, Power BI, Tableau) to create interactive dashboards.
  6. Problem-Solving: Ability to troubleshoot complex data-related issues and find innovative solutions.
  7. Communication: Excellent communication skills to collaborate effectively with cross-functional teams.
  8. Certifications: Preferred certifications (e.g., AWS Certified Data Engineer, Azure Certified Data Engineer, GCP Certified Professional Data Engineer).

Additional Skills (Preferred):

  1. Experience with data warehousing and data lake technologies (e.g., Google BigQuery, Amazon Redshift, Snowflake, Databricks)
  2. Knowledge of data analytics and machine learning concepts
  3. Familiarity with data governance and compliance frameworks (e.g., HIPAA, GDPR, CCPA)

Gov't mandated benefits

See also

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