Skills

Communication Python Scala Data Analysis SQL NoSQL Data Engineering Apache Kafka Apache Spark Monitoring Azure Data Factory Azure Cosmos DB Market research Problem-solving Research Database Management Machine Learning Programming Databases apache Analytical Skills SQL Server Azure AWS Agile Analytics Snowflake Talend Data Science Spark python programming Databricks PySpark Kafka Microservices Microsoft Azure Mathematics

Job Specifications

Being part of Air Canada is to become part of an iconic Canadian symbol, recently ranked the best Airline in North America. Let your career take flight by joining our diverse and vibrant team at the leading edge of passenger aviation.

The Data & AI Platform Developer (Data Engineer) will collaborate closely with other members of the enterprise Data & Analytics team in building the next generation of data management and ETL software to enable advanced analytics and data science across the company and our stakeholders. You are ready to be flexible and nimble in your work, from constructing Data Ingestion & ETL pipelines, building microservices and participating in exploratory data analysis with our Analytics team.

Responsibilities

Understand, implement and adapt to Air Canada best practices and frameworks in order to produce consistent, homogeneous solutions.
Design and develop pipelines that ingest data into a data lake either through batch processing and/or stream processing.
Design and develop ETL and/or ELT pipelines using multiple sources of data in various formats between data lake and data warehouse.
Conduct metadata management, data cleansing and conforming.
Use sound agile development practices (code reviews, testing, etc) to develop and deliver data pipelines.
Provide day-to-day support and technical expertise to both technical and non-technical teams.
Work with other engineers to brainstorm solutions to problems and support others in their goals.
Exhibit sound judgement, keen eye for details and tenacity for solving difficult problems.
Use strong analytical skills and support use of data for sound decision making.
Help build data engineering expertise and framework.
Develop expertise around the data and its workflows.
Collaborate with programmers, data analyst, data scientists and organizational leaders to identify opportunities for process improvements.
Translate business needs into technical requirements.
Build monitoring and debugging tools to analyze the data pipelines.
Generate datasets with machine learning tools to solve real time business problems.
Support the maturation of AI platforms, modules, and services that address cross-enterprise opportunities through market research and proof-of-concepts.
Discover opportunities to acquire new data from other systems.

Qualifications

Degree in Engineering, Computer Science or Mathematics/Statistics.
3-5 years of software engineering experience with a minimum of 1 year working with modern data platforms and cloud technology as a data engineer collaborating on the development and implementation of machine learning models.
Experience with cloud computing platforms such as Microsoft Azure and AWS.
Experience using modern data platforms and warehouses such as Snowflake and Databricks.
Proficiency in, or experience in, the following (or similar) technologies:
Relational database management systems and SQL-based data warehouses (e.g., Oracle, Snowflake, DB2, SQL Server).
Non-relational/NoSQL databases (e.g., Azure Cosmos DB).
Programming language for data manipulation and management, such as PySpark, SQL and Scala.
Python programming skills with experience in OOP, functional and/or analytical programming.
Data integration and orchestration platforms enabling ETL/ELT pipeline development such as Talend and Azure Data Factory.
Table format architectures such as Delta Lake and/or Apache Iceberg.
Apache Spark Structured Streaming and/or Apache Kafka Streams for data stream processing.
Track record working with data from multiple sources and willingness to dig-in and understand the data and to leverage creative thinking to deliver results.
Experience working in an Agile team environment.
Familiarity with data modeling patterns and data normalization rules.
Knowledge of the tooling for deployment, monitoring and site reliability.
Ability to work cooperatively with others on a team and be able to effectively drive cross-team solutions that have complex dependencies and requirements.
Excellent communication and problem-solving skills.
API development experience is an asset.
Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.
Knowledge of machine learning algorithms and agentic AI is a plus.

Conditions Of Employment

Candidates must be eligible to work in the country of interest at the time any offer of employment is made and are responsible for obtaining any required work permits, visas, or other authorizations necessary for employment. Prior to their start date, candidates will also need to provide proof of their eligibility to work in the country of interest.

Linguistic Requirements

Based on equal qualifications, preference will be given to bilingual candidates.

Diversity and Inclusion

Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees’ unique contributions to our company’s success.

As an equal

About the Company

Canada's largest airline, the country's flag carrier and a founding member of Star Alliance, the world's most comprehensive air transportation network celebrating its 25thanniversary in 2022, Air Canada provides scheduled passenger service directly to 51 airports in Canada, 51 in the United States and 86 internationally. It is the only international network carrier in North America to receive a Four-Star ranking from Skytrax, which in 2021 gave Air Canada awards for the Best Airline Staff in North America, Best Airline Staff... Know more

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