Job Title: Data Engineer
Location: 3 days onsite (Etobicoke)
Position Type: Expected 6-month contract 

Position Summary

Our client is looking to fill a contract position of a Data Engineer for Data Office – data engineering team that will bring new technologies and data insights to support their vision to create the airport of the future.  The bulk of the Data Engineer’s work would be in building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for key data and analytics consumers (like business/data analysts, data scientists or any persona that needs curated data for data and analytics use cases).
The Data Engineers will also need to guarantee compliance with data governance and data security requirements while creating, improving and operationalizing these integrated and reusable data pipelines. This would enable faster data access, integrated data reuse and vastly improved time-to-solution. The Data Engineer’s key to success will be their ability to integrate analytics and (or) data science results within our client’s business processes to support better planning and day-of operations management.
This role will require both creative and collaborative working with IT infrastructure teams and the wider business. It will involve evangelizing effective data management practices and promoting better understanding of data and analytics.
Additionally, the Data Engineer will also be expected to collaborate with data scientists, data analysts and other data consumers and work on the models and algorithms developed by them in order to optimize them for data quality, security and governance and put them into production leading to potentially large productivity gains.

Responsibilities and Activities

• Build data pipelines: Architecting, building infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Azure cloud and Microsoft Fabric technologies,  and ‘big data’ technologies and maintaining data pipelines will be the primary responsibility of the Data Engineer.
• Drive Automation through effective metadata management: The Data Engineer will be responsible for using tools and architectures to automate the most-common, repeatable, and tedious data preparation and integration tasks partially or completely in order to minimize manual and error-prone processes and improve productivity.
• Collaborate across departments: Data Engineer will work in close relationship with data science teams and with business (data) analysts in refining their data requirements for various data and data analytics and their data consumption requirements.
• Educate and train: The Data Engineer will be required to train data scientists, data analysts, or any data consumers about designed and developed data pipelining for their own use case integrations.
• Participate in ensuring compliance and governance during data use: Data Engineer should ensure that the data users pipeline design and development follow data governance and compliance.

Key Requirements

A successful candidate will have the expertise and skills described below:

Education and Training

• A bachelor's or master's degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field is required.
• The ideal candidate will have a combination of IT skills, data governance skills, and ETL development.

Previous Experience

• At least 8 years or more of work experience in data integration, data loads optimization and data quality.
• At least 5 years of experience working in cross-functional teams and collaborating with business stakeholders to drive tangible operational insights that have transformed a business’ operating model.

Technical and Business Knowledge/Skills

• Strong experience with advanced analytics tools for Object-oriented/object function scripting using languages such as PySpark Python, Java, Scala, Azure.
• Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
• The ability to work with both IT and business teams in integrating analytics and data science.
• Strong experience with popular database programming languages including SQL, PL/SQL for relational databases and NoSQL/Hadoop oriented databases for nonrelational databases.
• Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies.
• Strong experience in working with SQL, on Hadoop, open source, Microsoft technologies.
• Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production.
• Basic experience working with popular data discovery, analytics and BI software tools Tableau, MicroStrategy and PowerBI and for semantic-layer-based data discovery.
• Strong experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms.
• Demonstrated success in working with large, heterogeneous datasets to extract business value using popular data preparation tools.
• Demonstrated ability to work across multiple deployment environments.
• Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data managers and consumers across an organization
• Deep Airport/Transportation/Logistics knowledge or previous experience working in the business would be a plus.

Interpersonal Skills and Characteristics

• Strong experience supporting and working with cross-functional teams in a dynamic business environment.
•  An ideal candidate would be expected to collaborate with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly.
• Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.