Data Engineer

Full Time   |   San Francisco, CA

Position Overview:
The Data Engineer will support Glo’s data strategy and work with the Data Team supporting data pipelines, dashboards, models, and AI/ML projects as needed. This role will be responsible for enabling data-driven decisions across the Company by sourcing accurate data, building scalable infrastructure, and delivering analytics with predictive modeling. Use various methods to transform raw data into useful data systems, ultimately supporting the team to implement methods to improve data reliability, quality, and relevance.

Essential Functions and Responsibilities:
  • SQL :
    • Demonstrate advanced proficiency in SQL for efficient data extraction, transformation, and analysis.
    • Optimize SQL queries to ensure high performance and scalability.
  • Python:
    • Exhibit proficiency in Python programming for scripting and automation.
    • Familiarity with PySpark is preferred for enhanced data processing capabilities.
  • ETL Pipeline Development:
    • Design, develop, and maintain Extract, Transform, Load (ETL) pipelines
    • Ensure data quality and integrity throughout the ETL process.
  • Data Warehouse Management:
    • Take charge of managing and maintaining data warehouse performance to meet organizational requirements.
    • Proactively troubleshoot issues and implement enhancements to optimize data storage and retrieval.
  • Subscription Data Expertise:
    • Experience in user subscription data is preferred.
    • Showcasing a deep understanding of conversion, retention, and engagement metrics.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field
  • At least 5 years of experience in data science, machine learning, and statistical modeling
  • Proficient in programming languages such as Python, R, SQL, and SAS
  • Experience with data visualization tools such as Tableau, MixPanel, Google Looker
  • Strong understanding of statistical concepts and machine learning algorithms
  • Knowledge of data engineering and data warehousing concepts, including RedShift, Redshift Spectrum, AWS Glue,  AWS Lambda.
  • Excellent communication and presentation skills to convey technical concepts to non-technical stakeholders
  • Ability to work collaboratively in cross-functional teams and lead projects from ideation to implementation
  • Experience mentoring junior data engineers and guiding best practices in modeling and analysis
Preferred Qualifications:
  • Advanced Table Formatters
  • Showcase knowledge and experience in utilizing advanced table formatting such as Delta, Hudi, or Iceberg
  • Experience building ML Models for new Product Features & Fraud
  • Experience with Open Source Data Visualization tools
  • Experience with Databricks, Reverse ETL
Cultural Values Qualifications:
  • Start with the why
  • Drive change
  • Practice resilience
  • Embrace progress over perfection
  • Communicate openly
  • Win together
Disclaimer
The above job description is meant to describe the general nature and level of work being performed. It is not an exhaustive list of all responsibilities, duties and skills required for the position. Employees will be required to follow any other job-related instructions and to perform other job-related duties requested by their supervisor in compliance with Federal and State Laws.

All job requirements are subject to possible modification to reasonably accommodate individuals with disabilities. Some requirements may exclude individuals who pose a direct threat or significant risk to the health and safety of themselves or other employees.

Requirements are representative of minimum levels of knowledge, skills and/or abilities. To perform this job successfully, the employee must possess the abilities or aptitudes to perform each duty proficiently. Continued employment remains on an “at-will” basis.
 

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