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Added 4 mins ago
TC
Overnight Awake Residential Worker, Full-Time
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- Full-time
As a Certified B Corporation, we harness business for good. Since 1983 we’ve grown steadily, now delivering support across Alberta, British Columbia, and Ontario through more than 90…
Added 4 mins ago
TC
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Porter Airlines Inc.

Senior Developer, Data

250 Yonge Street, Suite 2800, Toronto, ON, M5B 2L7, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Sep 25, 2027
Experience: 5+ years of experience developing and supporting enterprise data platforms, data warehouses, lakehouses, or large-scale integration solutions
Posting language: English
Posted: Sep 25, 2026

Original job description

Job Summary

Reporting to the Director, Decision Intelligence and Emerging Technologies, the Senior Developer, Data provides technical leadership and hands-on expertise in designing, building, and maintaining key components of Porter’s enterprise data platform. This role is responsible for developing scalable data pipelines, ingestion frameworks, and transformation processes that enable trusted, accessible, and secure data across the organization including our AI program.

The Senior Developer, Data plays a key role in evolving Porter’s modern data lakehouse environments, supporting business intelligence, operational reporting, customer analytics, and emerging AI capabilities such as agents/coworkers and more. This role contributes to establishing engineering best practices across data for AI development, ensuring data products are reliable, observable, well-governed, and capable of supporting both current and future business needs.

Duties & Responsibilities

Lead the design and development of scalable data ingestion, transformation, and orchestration solutions within Porter’s data lakehouse environment focused on AWS S3 redshift
Develop and maintain batch and near real-time data pipelines that integrate data from operational systems, SaaS platforms, APIs, and third-party sources
Provide technical direction and mentorship to data developers, reinforcing engineering best practices, coding standards, and operational excellence
Partner with architects, technical leads, and business stakeholders to design data solutions aligned with enterprise architecture and business objectives
Design and implement reusable data models, transformation frameworks, and data products that support reporting, analytics, customer insights, and operational decision-making
Apply DevOps and CI/CD principles to automate data deployment, testing, monitoring, and lifecycle management of data assets
Establish and maintain data quality controls, PII validation processes, and automated testing frameworks to ensure trusted and reliable data
Implement data observability, lineage, and monitoring capabilities to proactively identify and resolve pipeline performance, reliability, and quality or compliance issues
Develop and optimize data solutions that support Customer, Revenue and Operations 360, enterprise analytics, and data integration of AI-enabled use cases
Ensure data assets are well-documented, discoverable, and governed through metadata management, cataloging, and business rule documentation
Collaborate with data analysts, data scientists, AI practitioners, and business teams to deliver accessible, high-quality datasets suitable for analytics, machine learning, and generative AI applications
Evaluate and recommend tools, frameworks, and technologies that improve platform scalability, developer productivity, and data accessibility
Support incident response, root cause analysis, and continuous improvement activities related to data platform operations
Actively participate in Porter’s Safety Management System (SMS) by reporting hazards and incidents encountered in daily operations and promoting a culture of safety
Perform other duties as assigned by the Director, Decision Intelligence and Emerging Technologies

Behavioural Competencies

Concern for Safety: Identifying hazardous or potentially hazardous situations and taking appropriate action to maintain a safe environment for self and others.
Teamwork: Working collaboratively with others to achieve organizational goals.
Passenger/Customer Service: Providing service excellence to internal and/or external customers (passengers).
Initiative: Dealing with situations and issues proactively and persistently, seizing opportunities that arise.
Results Focus: Focusing efforts on achieving high quality results consistent with the organization’s standards.
Fostering Communication: Listening and communicating openly, honestly, and respectfully with different audiences, promoting dialogue and building consensus.

Qualifications

5+ years of experience developing and supporting enterprise data platforms, data warehouses, lakehouses, or large-scale integration solutions
Understanding of the data foundations required to support analytics, machine learning, and generative AI solutions, including data quality, discoverability, lineage, and semantic consistency
Strong experience designing and developing data pipelines using modern cloud-based data using engineering tools and frameworks
Advanced SQ, Python,PySpark, sparkSQL skills with experience building complex transformations, optimization routines, and scalable data models, leveraging modern development practices and AI-assisted tools to improve productivity, quality, and maintainability
Proficiency in Python and experience developing automated data processing solutions
Experience working with cloud-based data platforms and services, preferably within AWS big data environments, Google GCP, Big query and GA4 is an asset
Hands-on experience with data integration, orchestration, and transformation tools such as AWS Datazone,Glue, AWS Lambda, Matillion, MuleSoft, or similar technologies
Strong understanding of data modeling concepts, including dimensional, operational, and analytical data structures
Experience implementing data quality, observability, lineage, and monitoring capabilities within modern data platforms
Knowledge of data governance, metadata management, privacy, security, and regulatory compliance practices
Proven ability to design and deliver scalable, maintainable, and secure data solutions
Demonstrated ability to lead technical discussions, mentor developers, and advise on engineering best practices
Strong problem-solving, troubleshooting, and performance optimization skills
Effective communication and collaboration within agile, cross-functional product teams
Experience working within a product operating model or closely with business stakeholders is an asset
Airline industry experience is an asset

Location

Toronto Downtown Office (250 Yonge Street)

Company Description

Since 2006, Porter Airlines has been elevating the experience of economy air travel for every passenger, providing genuine hospitality with style, care and charm. Porter’s fleet of Embraer E195-E2 and De Havilland Dash 8-400 aircraft serves North America, including a coast-to-coast domestic Canadian network, the U.S., Mexico, the Caribbean and Central America. Headquartered in Toronto, Porter is an Official 4 Star Airline® in the World Airline Star Rating®. Visit www.flyporter.com or follow @porterairlines on Instagram, Facebook and X.

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More about this job

Responsibilities

The Senior Developer, Data will lead the design and development of scalable data ingestion, transformation, and orchestration solutions within the company's data lakehouse environment. They are responsible for mentoring data developers, establishing engineering best practices, and ensuring data products are reliable, observable, and well-governed.

Requirements

Candidates must have 5+ years of experience in enterprise data platforms, data warehouses, or large-scale integration solutions. Proficiency in Python, SQL, PySpark, and cloud-based data environments like AWS is required, along with strong skills in data modeling and pipeline optimization.

Skills

Data Engineering
Python
SQL
PySpark
AWS
Data Lakehouse
Data Pipelines
ETL
Data Modeling
Cloud Computing
DevOps
CI/CD
Data Governance
Data Quality
Mentorship
Technical Leadership

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
AWS
Redshift
S3
Python
SQL
PySpark
SparkSQL
Data Lakehouse
ETL
DevOps
CI/CD
Data Governance
Data Quality
Metadata Management
Data Observability
Machine Learning
Generative AI
Big Data
GCP
BigQuery
GA4
AWS Datazone
AWS Glue
AWS Lambda
Matillion
MuleSoft
Agile
Data Modeling
API

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