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Senior Developer (Lending Data Engineering)
Farm Credit Canada —Canada
- $107,780–$145,820 a year
- Full-time
- Hybrid work
- Computer Science
- Engineering
- English
11d

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Senior Developer (Lending Data Engineering)

Farm Credit Canada
Canada

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Job details

Full-time
11 days ago

Skills

Data modeling
Computer Science
Software Engineering
Engineering
English
SQL
OOP
AWS
Bachelor's
Continuous integration
Software development
S3
Financial services
Integration testing
Business management
TypeScript
Data warehouse
Python
Design patterns

Full job description

Closing Date (MM/DD/YYYY):

06/26/2026

Worker Type:

Permanent

Language(s) Required:

English

Term Duration (in months):

Salary Range (plus eligible to receive a performance based incentive, applicable to position) :

$107,780 - $145,820

Why FCC?

At FCC, we’re proud to be 100% invested in Canadian agriculture and food. As a federal Crown corporation, we provide financing, knowledge resources and business management software to over 103,000 customers nationwide.

Here’s what you can expect when you join our team:

Competitive total rewards packages: market-aligned and performance-based salary and incentive programs, flexible and comprehensive group benefit and savings plans, and well-being support through benefits and wellness programs
Purpose-driven work: We build strong relationships, share knowledge and support the people who feed the world
Growth: Learning and development opportunities to help you thrive
Hybrid work options

How you'll make an impact

Put your engineering expertise into practice by so lving compl icated pr oblems in our internal lending software by building reliable and modern data pipelines and making a meaningful impact through both technical leadership and collaboration .

As a Senior Developer, you’ll play a critical role in ensuring FCC’s lending data is trusted, accurate , timely , and ready to drive decision-making across the organization. As a senior technical contributor and informal technical lead, you will design and build modern, cloud-based data pipelines that move loan-related data from lending systems into the enterprise Business Vault using Data Vault 2.0 methodologies. Your work will directly enable high‑quality reporting, risk analysis, and financial insights that support FCC’s business and strategic objectives .

In this role, you’ll collaborate closely with product owners, analysts, architects, and other developers to design end‑to‑end data solutions, while also remaining hands‑on with coding, testing, and deployment. Beyond delivery, you’ll guide and mentor other developers by sharing best practices, influencing architectural decisions, and promoting strong engineering and data development standards.

What you'll do

Develop, test, and deploy high‑quality code using Python, PySpark , and SQL in a cloud‑based environment
Lead technical and solution design session within an agile development team
Influence and champion the vision for data engineering across sever al Lending teams
Use modern data engineering practices and Data Vault 2.0 methodologies to design, build, and maintain ETL data pipelines
Ensure technical solutions , pipelines and data models are fit for purpose, aligned with enterprise standards, and maintained in the most efficient and effective manner
Collaborate closely with product owners, analysts, architects, and internal data consumers across Reporting, Risk, and Finance.
Act as an informal technical leader by mentoring and coaching developers, leading code reviews and providing constructive feedback to team members
Improve pipeline reliability and maturity by enhancing automation, integration testing, and CI practices across the data development lifecycle

What you'll bring to the team

Required q ualifications

Bachelor’s degree in computer science or software engineering
Minimum 10 years of software development experience (or an equivalent combination of education and experience)
Expert-level proficiency in some or all of the following AWS technologies: AWS Glue, Step Functions, S3, Redshift, Quicksight , Lambda, Eventbridge , Sagemaker , and AppFlow
Expert level proficiency in Python and/or PySpark
Extensive experience designing and building ETL data pipelines
Data modelling experience in both Data Vault 2.0 and Dimensional (Star Schema) methodologies
Proven knowledge of common design patterns and when to apply them, such as object-oriented programming (OOP) and functional programming (FP) paradigms
Experience optimizing design to enable business value creation
Demonstrated experience with application design and system integration
Demonstrated experience with modern approaches to code reviews, version control and continuous integration
Foundational knowledge of financial services concepts such as loans, credit scores, and risk data

Preferred q ualifications

Experience coaching and mentoring peers (informal leadership)
Experience building automation and integration tests and designing easy-to-use frameworks
Working knowledge of Typescript

Not sure you meet every requirement? We encourage you to apply anyway.

#FCCEN

You belong here
At FCC, we’re committed to creating an inclusive, equitable and accessible workplace – one that reflects the communities where we live, work and play. Our team is made stronger through diversity, and we’re dedicated to building a workforce that brings together a range of backgrounds, abilities and perspectives.

We encourage qualified applicants to apply, including members of these four employment equity groups:
• Indigenous Peoples
• Members of visible minority groups
• Persons with disabilities
• Women

Accessibility and accommodations

To support an inclusive and accessible candidate experience, we encourage anyone needing an adjustment or accommodation during any stage of the recruitment process to email us at: [email protected] . An HR partner will respond and work with applicants who request a reasonable accommodation. Information received in relation to accommodation requests will not impact hiring decisions.

Work Location: Hybrid remote in Canada

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Senior Developer (Lending Data Engineering)

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