Senior Developer, Data

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