Data Engineer

Charger Logistics Inc. is a world-class, asset-based carrier with locations across North America. With over 20 years of experience in providing top-tier logistics solutions, Charger Logistics has evolved into a world-class transport provider and continues to grow. Charger Logistics invests in its employees, providing opportunities for learning and growth, and fostering their expertise and career advancement. We are an entrepreneurial-minded organization that warmly welcomes and supports individual ideas and strategies. We are currently expanding and are looking to add a dedicated and experienced Data Engineer to our team. Responsibilities: - Understand the business requirements and processes around advanced analytics model execution. - Develop end-to-end data pipelines from ingestion to visual analytics using Python, SQL, and Snowflake. - Manage, enhance, maintain, and support our Snowflake-based data lake. - Support our business intelligence developers to generate stunning visual analytics. - Develop, maintain and support our library of analytical functions written in Python, SQL, Snowflake, PySpark, and Matillion. - Participate in our quick-paced, agile data iteration to deliver new capabilities on time. - Utilize key features of Snowflake for processing, entitlements, ingestion, transformation, and data sharing. - Collaborate with data scientists, financial data analysts, software engineers, and other data engineers to implement robust solutions that leverage cloud, big data, NLP, and ML. - Construct machine learning models with advanced analytics methods to extend our capabilities and deliver new business value. - Record and demonstrate data-driven business insights. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation. - Work closely with software engineering teams to facilitate real-time model implementations and the creation of new features. - Leverage current data sources, mine data from new sources, identify avenues for primary data gathering, and provide recommendations on scaling new methods more broadly. Requirements: - A university degree or equivalent in data analytics, statistics, math, or computer science, with at least 3 years of relevant experience. - Minimum of 3 years of hands-on Snowflake Practitioner experience in a Data Engineering role. - Snowflake Certification or Snowflake experience is required. SnowPro® Advanced: Data Engineer Certification is preferred. - Excellent knowledge of Python, Matillion, and SQL - Experience with Azure ML Studio is preferred. - Familiarity with Airflow and Matillion Studio is beneficial. - Experience in big data processing and the development of Python and SQL for extensive data quantities. - Considerable experience with unit and integration testing. - Excellent analytical, storytelling, and problem-solving skills. - Ability to explain analytics recommendations to both technical and non-technical team members. - Strong understanding of quantitative (univariate and multivariate) analysis techniques. - Experience with predictive modeling and machine learning. - Proven experience with statistical analysis methods, data mining, machine learning, and predictive models using Python, R , PySpark, Matillion, or similar tools. - Experience using scripting language for data collection, organization, and manipulation. - Ability to work with data with significant ambiguity, develop creative approaches to analytical problems, and interpret data and results from a business/industry perspective. Benefits: - Health Benefits - Career Growth - High Competitive Salary