Senior Data Engineer
Cooke Aquaculture Inc. City of Saint John, New Brunswick, Canada
Food and Beverage Manufacturing · 10,001+ employees
About the role
The Senior Data Engineer will design, build, and optimize scalable data pipelines, APIs, and data models to support enterprise analytics and operational reporting. They will also collaborate with cross-functional teams to implement automated data quality monitoring, lineage, and governance standards.
What they look for
Requirements
Candidates must have a bachelor's degree in a technical discipline and 4–7 years of progressive experience in data engineering or integration. Proficiency in SQL, Python, and cloud-based data tools like Snowflake and DBT is required.
Benefits
Full description
Cooke is a global seafood company with operations in North America, Europe, South America and Australia. Our company’s success is driven by our dynamic, highly skilled, and innovative management team, supported by dedicated employees who live in coastal communities and contribute to the local area’s economy and sense of community.
Cooke is continuing to mature its digital strategy through modern data platforms, integrated data pipelines, and enterprise data standards that support operations, processing, distribution, and corporate functions. As a Senior Data Engineer, you will design scalable data pipelines, integrations, APIs, and models that support enterprise analytics, operational reporting, and data platform maturity while mentoring others and helping align solutions to Cooke’s data architecture, security, governance, and quality standards.
The Role
As a Senior Data Engineer, you will design, build, and optimize reliable data pipelines, integrations, APIs, and data models across Cooke’s modern data ecosystem. You will work with limited direction to translate complex business and technical requirements into secure, scalable, well-documented solutions, while partnering with architects, analysts, engineers, application teams, and data stakeholders to improve data quality, performance, automation, lineage, and reuse across domains.
Key Responsibilities
- Design scalable APIs, data pipelines, integrations, and transformations aligned to Cooke’s data architecture, security, and enterprise standards.
- Develop optimized logical and physical data models that support analytics, reporting, integration, and reuse across business domains.
- Design automated cleansing, validation, profiling, orchestration, and data quality monitoring processes within data workflows.
- Analyze trends, data quality metrics, performance issues, and pipeline reliability to recommend and implement sustainable improvements.
- Collaborate with architects, data owners, analysts, application teams, and engineers to integrate multiple tools and systems for end-to-end data movement.
- Maintain high-quality technical documentation, metadata, lineage, technical specifications, and reusable patterns to support ongoing operations and knowledge sharing.
What Success Looks Like
- Scalable and reusable data pipelines, APIs, and integrations are designed and delivered with strong reliability, security, and performance.
- Data models, data flows, and lineage are well understood, documented, and aligned to enterprise data architecture standards.
- Automated cleansing, profiling, orchestration, and quality monitoring improve data trust, issue resolution, and operational efficiency.
- Complex data quality, performance, and integration challenges are analyzed, resolved, and translated into sustainable improvements.
- Cross-functional stakeholders have confidence in the accuracy, usability, documentation, and supportability of delivered data solutions.
Core Skills & Competencies
- Proficient in designing scalable data pipelines, APIs, integrations, orchestration workflows, and automated transformations using tools such as Snowflake, DBT,FiveTran, Boomi, Azure Data Factory, SQL, Python, and related technologies.
- Strong ability to design logical and physical data models, map dataflowsand lineage, and align solutions to enterprise data architecture and integration standards.
- Advanced working knowledge of data cleansing, profiling, validation, metadata management, data quality monitoring, data security, governance workflows, and secure data transfer patterns.
- Ability to diagnose complex data quality, performance, and reliability issues and implement sustainable technical improvements across data platforms and integrations.
- Strong collaboration, documentation, mentoring, and communication skills to guide stakeholders, support junior team members, and promote reusable data engineering patterns.
Behaviors That Drive Success
- Adaptability: Adapts quickly to new processes, systems, or business needs andremainsproductive in ambiguity.
- Business Acumen: Applies business insights to improve processes and make informed decisions.
- Collaboration & Synergy: Builds strong cross-functional relationships and encourages knowledge sharing.
- Decisiveness: Makestimely, data-informed decisions within scope.
- Design Thinking: Uses user-centered design and data insights to inform solutions.
- Digital Acumen: Applies digital insights to improve work quality or customer experience.
- Diversity Mindset: Values diversity in teams and ensures inclusivity in discussions and decisions.
- Growth Mindset:Demonstratescontinuous learning and encourages it in others.
- Innovative: Applies innovative methods to solve functional or business challenges.
- Outcome Driven: Delivers measurable results tied to team or project outcomes.
- Political Savviness: Navigates relationships within the team and immediate area.
- Risk Taking: Takes calculated risks within role boundaries.
Experience & Qualifications
- Education:Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related technical discipline, or equivalent experience.
- Experience: 4–7 years of progressive experience in data engineering, data integration, analytics enablement, or related technical roles, including experience designing and improving production data pipelines.
- Skills: Strongproficiencyin SQL, Python or comparable scripting, ETL/ELT design, data modelling, API integration, orchestration, pipeline automation, data quality management, and cloud data platform concepts.
- Organization-specific: Hands-on experience with Cooke’s data tools and patterns, including Snowflake, DBT,FiveTran, Boomi, Azure Data Factory, governance and metadata practices, MDM integrations, and alignment to Cooke’s enterprise data model and security standards.
Join our team and enjoy the benefits of full-time year-round employment with competitive rates and a comprehensive benefits package tailored to support your well-being and career growth.
Benefits Package:
- Health Benefits:Includes coverage for dental, vision, and extended medical care.
- Insurance:Life and disability insurance provided for financial security.
- Support Services:Access to an Employee Assistance Program (EAP).
- Financial Planning:Opportunity for RRSP matching to support your retirement savings.
- Time Off:Paid vacation, holidays, and sick leave for work-life balance.
- Wellness:Wellness programs and access to on-site gym facilities (available in some locations).
- Career Development:Professional growth opportunities and avenues for advancement.
- Perks:Employee discounts on company products or services.
- Convenience:On-site parking or parking allowance.
If you're looking to join a supportive team environment with opportunities for personal and professional development, apply now and become part of our dynamic team.
The Why
Why Cooke? Simple - because we are a company that rewards initiative, resourcefulness, and work ethic. We will champion your growth and provide you with the platform to create your path, your career, and your future.
NOTE: The recruiter is reviewing and interviewing eligible applicants for this position as they are received. If you are interested in this posting, you are encouraged to apply as soon as possible.
#cooke-dnp
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