Data Engineer

hace 6 días

Bogotá, Bogotá D.E., Colombia Charger Logistics A tiempo completo
About Charger Logistics

Charger Logistics Inc. is a world-class asset-based carrier with a strong presence across North America. With over two decades of experience providing top-notch logistics solutions, Charger Logistics has evolved into a leading transport provider, continuously expanding its capabilities.

Our Culture

We are an entrepreneurial-minded organization that fosters a culture of innovation and collaboration. We invest time and resources into our employees, providing them with opportunities to learn and grow their expertise. Our team is passionate about delivering exceptional results and is committed to supporting individual ideas and strategies.

Job Summary

We are seeking a highly motivated and experienced Data Engineer to join our team. As a Data Engineer at Charger Logistics, you will play a critical role in developing and maintaining our advanced analytics capabilities.

Key Responsibilities
  • Advanced Analytics Model Execution
    • Understand business requirements and processes around advanced analytics model execution.
  • Data Pipeline Development
    • Develop end-to-end data pipelines from ingestion to visual analytics using Python, SQL, and Snowflake.
  • Data Lake Management
    • Manage, enhance, maintain, and support our Snowflake-based data lake.
  • Business Intelligence Support
    • Support our business intelligence developers to provide stunning visual analytics.
  • Library Development
    • Develop, maintain, and support our library of analytical functions written in Python, SQL, Snowflake, PySpark, and Matillion.
  • Snowflake Expertise
    • Leverage key features of Snowflake for processing, entitlements, ingestion, transformation, and data sharing.
  • Collaboration and Innovation
    • Collaborate with data scientists, financial data analysts, software engineers, and other data engineers to implement powerful solutions that leverage cloud, big data, NLP, and ML.
  • Machine Learning Model Development
    • Build machine learning models with advanced analytics techniques to extend our capabilities and deliver new business value.
  • Data-Driven Insights
    • Capture and present data-driven business insights.
  • Process Automation
    • Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation.
  • Real-Time Model Implementations
    • Work closely with software engineering teams to drive real-time model implementations and new feature creations.
  • Data Source Identification
    • Leverage existing data sources, identify and mine data from new sources, identify opportunities for and execute primary data gathering efforts, and provide recommendations on scaling new methods more broadly.
Requirements
  • Education and Experience
    • University degree or equivalent in data analytics, statistics, math, or computer science, with a minimum of 3 years relevant experience.
  • Snowflake Expertise
    • 3+ years of hands-on Snowflake Practitioner experience in a Data Engineering role.
  • Certifications
    • Must be Snowflake Certified or should have experience in Snowflake. The SnowPro Advanced: Data Engineer Certification is preferred.
  • Technical Skills
    • Excellent knowledge of Python, Matillion, and SQL.
  • Desirable Skills
    • Experience on Azure ML Studio is Preferred.
    • Good to have experience in Airflow and Matillion Studio.
    • Experience in big data processing and the development of Python and SQL for large amounts of data.
    • Considerable experience with unit and integration testing.
  • Soft Skills
    • Excellent analytical, storytelling, and problem-solving skills.
    • Ability to translate/communicate analytics recommendations to both technical and non-technical team members.
    • Strong understanding of quantitative (univariate and multivariate) analysis techniques.
    • Experience with predictive modelling and machine learning.
    • Strong experience with statistical analytical techniques, data mining, machine learning, and predictive models using Python, R, PySpark, Matillion, or similar tools.
    • Experience using scripting language for collecting, organizing, and manipulating data.
    • Ability to work with data with significant ambiguity, develop creative approaches to analytical problems, and interpret data and results from a business/industry perspective.

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