Senior Data Engineer

4 weeks ago


Tate, United States TechnoGen Full time
Job Summary

The Senior Data Engineer will play a key role in transforming data from disparate systems to provide actionable insights and analytics for business stakeholders. This individual will leverage cloud-based infrastructure to implement scalable, resilient, and efficient technology solutions. Collaborating with cross-functional teams and business leaders, the Senior Data Engineer will architect, design, implement, and operate data engineering solutions using Agile methodology. Key responsibilities include leading technical projects, mentoring junior team members, and advancing new technologies to improve data quality and reliability.

Responsibilities:
  • Design and implement data engineering solutions using cloud-based infrastructure
  • Collaborate with cross-functional teams and business leaders to drive business outcomes
  • Lead technical projects and mentor junior team members
  • Advance new technologies to improve data quality and reliability

Requirements:
  • Bachelor of Science degree in Computer Science or equivalent
  • At least 7 years of post-degree professional experience
  • At least 5+ years of Airline industry experience
  • 4+ years development experience building and maintaining ETL pipelines
  • 3+ years of experience working with database technologies and data development
  • Experience in mentoring junior team members through code reviews and recommending adherence to best practices
  • Deep understanding of writing test cases to ensure data quality, reliability, and high level of confidence
  • Track record of advancing new technologies to improve data quality and reliability
  • Continuously improve quality, efficiency, and scalability of data pipelines
  • Expert skills working with queries/applications, including performance tuning, utilizing indexes, and materialized views to improve query performance
  • Identify necessary business rules for extracting data along with functional or technical risks related to data sources
  • Develop initial queries for profiling data, validating analysis, testing assumptions, driving data quality assessment specifications, and define a path to deployment
  • Familiar with best practices for data ingestion and data design

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