Data Engineering Expert
- Montreal, QC, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- 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.
Daily Responsibilities
Education & Experience
Although all applications are carefully analyzed, we will communicate only with those selected. Thank you for your interest in Croesus.
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.
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.
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.
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.
- 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.
- 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.
- 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
Although all applications are carefully analyzed, we will communicate only with those selected. Thank you for your interest in Croesus.
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
Design, develop, optimize, and operate scalable Databricks Lakehouse data pipelines, including migration, Spark processing, governance, and data quality. Implement orchestration, monitoring, and alerting; resolve production incidents and collaborate with cross-functional teams to deliver reliable, documented data models.
Requirements
Requires a bachelor’s degree in computer science, software engineering, computer engineering, or a related field, and at least five years of data engineering or analytical solution development experience. Candidates should have production experience with Databricks, proficiency in Python and Spark, and knowledge of Lakehouse architectures, pipeline orchestration, governance, metadata management, and DataOps/DevOps practices.
Skills
- Data Engineering
- Databricks
- Python
- Apache Spark
- Lakehouse Architecture
- Medallion Architecture
- ETL/ELT Pipelines
- Data Pipeline Orchestration
- Unity Catalog
- Data Governance
- Metadata Management
- Data Quality
- DataOps
- DevOps
- Monitoring and Observability
- Incident Resolution
Benefits
- Flexible Vacation
- Corporate Profit-Sharing Plan
- Hybrid Work
- Sports Program
- Gym Access
- Telemedicine
- Group Insurance
- Group RRSP
- Ongoing Training and Development
- Referral Bonus
- Indoor and Outdoor Parking
- Electric Vehicle Charging
- Complimentary Breakfast
- Social Events
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Engineering
Keywords
- Databricks
- Python
- Apache Spark
- Lakehouse
- Medallion Architecture
- Bronze Layer
- Silver Layer
- Gold Layer
- ETL
- ELT
- Data Pipelines
- Unity Catalog
- Data Governance
- Metadata Management
- Data Quality
- Data Lineage
- Data Orchestration
- Monitoring
- Observability
- Alerting
- Production Support
- Incident Management
- DataOps
- DevOps
- Distributed Data Processing
- Data Migration
- Analytics
- Artificial Intelligence
- SaaS
- Multi-Tenant Environments