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Data Engineering Expert

  • Montreal, QC, Canada
  • Laval, QC, Canada

Full-time

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Job details

Job type
Full-time
Experience
Experience: Minimum of 5 years of experience in data engineering or analytical solution development, including hands-on experience designing and operating data pipelines.
Posting language
English
Posted

Original job description

Company Description


Croesus provides innovative, high-performance, and secure wealth management solutions that include portfolio management systems, portfolio rebalancing tools, and application programming interfaces (APIs). These solutions empower wealth management professionals to improve their productivity, enhance their client relationships, make informed decisions, and maximize the management of their assets under management.


Croesus’s mission is to provide a superior experience to its clients, users, partners, and employees and to positively impact the community. With more than 200 employees in its Montréal, Toronto, and Geneva offices, Croesus has won several industry awards for being a high-quality solution provider and an outstanding employer.


Position


Job Overview:


The Data Engineering Expert designs, develops, and optimizes the company's data pipelines and analytical architectures within a modern, Databricks- focused Lakehouse environment. They ensure the collection, transformation, governance, and high availability of reliable data to power analytics and artificial intelligence solutions. The incumbent also ensures the operational performance, stability, and incident resolution for production data flows.


Your Daily Responsibilities:

  • Lakehouse Architecture & Development: Design, optimize, and maintain scalable and high-performing data pipelines (ELT/ETL) by implementing the Medallion architecture (Bronze, Silver, Gold layers) and Spark distributed processing on Databricks.
  • Modernization & Migration: Analyze and migrate existing data pipelines to the Databricks platform while optimizing storage and processing times.
  • Governance & Quality: Apply governance and metadata management standards (notably via Unity Catalog) to ensure constant data quality and traceability across datasets.
  • Operations, Observability & Support: Implement automated pipeline orchestration, monitoring, and alerting, and actively investigate and resolve production incidents.
  • Cross-Functional Collaboration: Partner with Product, Innovation, Data, and Systems teams to translate business requirements into reliable, well-documented data models.

What We Are Looking For


Strong proficiency in French is mandatory as all internal meetings are conducted in French.

Education & Experience:

  • Education: Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related field.
  • Experience: Minimum of 5 years of experience in data engineering or analytical solution development, including hands-on experience designing and operating data pipelines.
  • Technical Expertise: Hands-on production experience with Databricks handling large data volumes (strongly preferred).
  • Assets: Experience in SaaS/multi-tenant environments or AI-related projects.

Technical Skills:

  • Languages & Frameworks: Proficiency in Python and distributed data processing frameworks (Spark).
  • Architectures & Data Flows: Strong understanding of Lakehouse architectures, ELT/ETL pipeline design, and orchestration mechanisms.
  • Governance & DevOps: In-depth knowledge of Unity Catalog (or equivalent), metadata management, and DataOps/DevOps practices.
  • Monitoring: Hands-on experience implementing monitoring, observability, and alerting strategies.

Soft Skills:

  • Rigor & Autonomy: Strong sense of accountability, commitment to data quality, and design rigor.
  • Problem Solving: Strong analytical mindset when addressing complex challenges, with an automation-first approach.
  • Teamwork: Excellent communication skills and proven ability to collaborate effectively across diverse technical teams.

Why Join Croesus?

  • À la carte vacations
  • Annual salary + Corporate profit-sharing plan
  • Hybrid work, 2 days a week in office (Laval & Montreal offices)
  • Sports program
  • Gym available at our Laval head office
  • Telemedicine + group insurance (super useful for the family 😉)
  • Group RRSP
  • Proximity to Montmorency & Mcgill metro
  • Ongoing training and development plan
  • Referral bonus
  • Indoor and outdoor parking & electric car recharging
  • Croesus boutique
  • Beautifully renovated and spacious office
  • Complimentary breakfast every morning
  • 2X per month, Happy hours, prepared by our Croesus Life Partner


Are you interested in this challenge? Do you believe you have the qualities and expertise required for this position? Please complete your application today.


Although all applications are carefully analyzed, we will communicate only with those selected. Thank you for your interest in Croesus.

More about this job

Responsibilities

The Data Engineering Expert designs, develops, and optimizes scalable data pipelines and analytical architectures within a Databricks Lakehouse environment. They are responsible for ensuring data quality, governance, and operational stability while collaborating with cross-functional teams to support analytics and AI solutions.

Requirements

Candidates must hold a bachelor's degree in a relevant field and possess at least 5 years of experience in data engineering. Proficiency in Python, Spark, and Databricks is required, along with strong communication skills in French.

Skills

  • Data engineering
  • Databricks
  • Lakehouse architecture
  • Python
  • Spark
  • ETL
  • ELT
  • Unity Catalog
  • Data governance
  • Data modeling
  • DevOps
  • DataOps
  • Metadata management
  • Distributed processing
  • Pipeline orchestration
  • Analytical solution development

Benefits

  • A la carte vacations
  • Corporate profit-sharing plan
  • Hybrid work
  • Sports program
  • Gym access
  • Telemedicine
  • Group insurance
  • Group RRSP
  • Referral bonus
  • Indoor and outdoor parking
  • Electric car recharging
  • Complimentary breakfast
  • Happy hours

Visa sponsorship

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Categories

  • Data & Analytics
  • Software
  • Engineering
  • Technology
  • Finance & Accounting

Keywords

  • Data Engineering
  • Databricks
  • Lakehouse
  • Medallion Architecture
  • Spark
  • Python
  • ETL
  • ELT
  • Unity Catalog
  • Data Governance
  • DataOps
  • DevOps
  • Metadata Management
  • Data Pipelines
  • Distributed Processing
  • Analytics
  • Artificial Intelligence
  • SaaS
  • Multi-tenant
  • Data Modeling
  • Observability
  • Automation
  • Wealth Management
  • API
  • Portfolio Management

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