Recherche d'emploi > Brampton, ON > Data engineer

Data Engineer

Charger Logistics
Brampton, ON, Canada
70K $-95K $ / an (estimé)
Temps plein

Charger Logistics is a world class asset-based carrier. We specialize in delivering assets, on time and on budget. With the diverse fleet of equipment, we can handle a range of freight, including dedicated loads, specialized hauls, temperature-controlled goods and HAZMAT cargo.

Charger logistics invests time and support into its employees to provide them with the room to learn and grow their expertise and work their way up.

We are entrepreneurial-minded organization that welcomes and support individual idea and strategies.

We are looking for a Data Engineer who would be a part of a high-powered, globally distributed team (Data Science & BI Engineering) that builds end-to-end data pipelines, develops complex analytical processes, and manages our central data lake for advanced analytics.

The team also develops visual analytics with Tableau. The candidate will work cross-functionally with technical and non-technical teams to take on a variety of tasks including but not limited to mining data, building models, building dashboards, and conducting detailed analysis.

The ideal candidate will have a analytical mindset, deep understanding of databases, visualization, and modeling techniques, and the ability to thrive in a dynamic, fast-paced environment delivering against tight deadlines.

Responsibilities :

  • Understand the business requirements and processes around advanced analytics model execution.
  • Develop end-to-end data pipelines from ingestion to visual analytics with Python, SQL and Snowflake.
  • Experience on Matillion Studio is Preferred.
  • Good to have experience in Airflow.
  • Manage, enhance, maintain and support our Snowflake-based data lake.
  • Support our business intelligence developers to provide stunning visual analytics.
  • Develop, maintain and support our library of analytical functions written in Python, SQL and Snowflake.
  • Leverage 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 powerful solutions that leverage cloud, big data, NLP and ML.
  • Build machine learning models with advanced analytics techniques to extend our capabilities and deliver new business value.
  • Capture and present 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 drive real-time model implementations and new feature creations.
  • 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 :

  • University degree or equivalent in data analytics, statistics, math, or computer science, with a minimum of 3 years relevant experience.
  • Excellent knowledge of Python and SQL.
  • Experience in big data processing and the development of Python and SQL for large amounts of data.
  • Considerable experience with unit and integration testing.
  • Excellent analytical, storytelling, and problem-solving skills.
  • Ability to translate / communicate analytics recommendations to both technical and nontechnical 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 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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Il y a plus de 30 jours
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