Senior Data Engineer

Orca Intelligence

London

On-site

CAD 120,000 - 160,000

Full time

14 days+

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Benefits offered by this job

RRSP contribution matching

Fantastic benefits package

Lifestyle Spending Account

Complimentary cell phone plan

Profit based bonus plan

Job summary

A leading data analytics firm located in London, Ontario is seeking a Mid-Senior Level Data Engineer to lead the rebuild of its data platform. This role involves ensuring data accuracy and automation processes while collaborating with internal and external partners. Key qualifications include 6+ years of data platform experience, expertise with Azure SQL, and strong scripting skills. The role offers a full-time position with a competitive benefits package and an RSU contribution matching program.

Qualifications

6+ years in data engineering / data platform roles.
Strong expertise with Azure SQL and SQL Server.
Hands-on experience with Azure data tools.
Excellent SQL and at least one scripting language (Python preferred).
Proven ability to design end-to-end data pipelines and migrate legacy data environments.

Responsibilities

Lead the assessment of Orca’s current data landscape.
Design and implement a modernized data platform architecture.
Build, maintain, and optimize ETL/ELT pipelines.
Automate manual data processes and reports where possible.
Own performance, reliability, and capacity planning of the platform.
Collaborate with analysts, external advisors, and cross-functional teams.
Support data governance, naming conventions, and access controls.

Skills

Data engineering

Azure SQL

SQL Server performance tuning

Python

ETL/ELT pipeline design

Automation

Python

ETL/ELT pipelines

Data governance

Tools

Azure Data Factory

Databricks

Power BI

Job description

Orca has been providing freight audit and analytics services to its growing client base since 2016. We have experienced tremendous growth since inception and are proud to offer our solution to some of North America’s largest organizations. Orca processes billions of dollars in freight invoices each year for clients and provides invaluable reporting and analysis to help our clients operate more efficiently. Orca was awarded London’s prestigious ‘Medium Business of the Year’ award in 2024 by the London Chamber of Commerce for tremendous growth and community involvement.

Job Summary

The successful candidate will be responsible for leading the rebuild of Orca’s data platform. Working with our existing Azure SQL, SQL Server on Azure VMs, and Azure Fabric environment, this role will assess what is working, identify gaps and risks, and design and implement improved data architecture and pipelines. The candidate will work closely with external data architecture partners, our internal analytics team, and key stakeholders to deliver a modern, scalable, and reliable data platform that supports both internal operations and client‑facing analytics.

The candidate will act as the technical owner of Orca’s data platform, ensuring that data is accurate, timely, and accessible, while reducing manual processes through automation. The successful candidate may also support and take on responsibilities including performance tuning, reliability, and general data operations.

Responsibilities

Lead the assessment of Orca’s current data landscape (Azure SQL, SQL Server on Azure VMs, Azure Fabric, and related integrations) and document strengths, weaknesses, and risks
Design and implement a modernized data platform architecture in partnership with external advisors and internal stakeholders
Build, maintain, and optimize ETL/ELT pipelines to ingest, transform, and deliver data for analytics and operational needs
Standardize and automate manual data processes, reports, and extracts wherever possible
Own database performance and reliability, including indexing, query optimization, capacity planning, and environment management
Implement and manage backup, restore, and disaster recovery processes for critical data systems
Collaborate closely with our team of data and business analysts to ensure they have clean, well‑modeled, and well‑documented data for Power BI and other reporting tools
Establish and maintain data quality checks, monitoring, and alerting for key data flows
Contribute to data governance practices, including naming conventions, documentation, and data access controls
Provide technical guidance and best practices to internal teams on data‑related topics and support broader data initiatives as required

Qualifications

6+ years in data engineering / data platform roles, ideally in a SaaS or analytics‑heavy environment.
Strong expertise with Azure SQL and SQL Server (performance tuning, indexing, query optimization).
Hands‑on experience with Azure data tools such as Azure Data Factory, Databricks, Synapse, and related services.
Excellent SQL skills and strong comfort with at least one scripting language (Python preferred; PowerShell or .NET a plus).
Proven track record of designing and implementing data pipelines end‑to‑end.
Migrating from legacy data environments to more modern, centralized platforms.
Automating manual data workflows.

The following qualifications are not required, however would be considered a strong asset:

Experience with Azure Fabric specifically (lakehouse, medallion architecture, etc.).
Exposure to Power BI models and how engineers can best support BI teams.
Experience introducing CI/CD for data (e.g., Git‑based deployments of pipelines and database changes).
Background covering or collaborating closely with DBA responsibilities (or prior role as a DBA who shifted into data engineering).
Experience in a regulated or audited environment (SOC, ISO, etc.) and handling PII or financial data.

Key Traits

Systems thinking – sees how source systems, pipelines, databases, and reports fit together and designs solutions that work end‑to‑end.
Pragmatism – balances “ideal” architecture with practical constraints, making incremental improvements that deliver value quickly.
Ownership mindset – treats the data platform as their product, taking responsibility for reliability, performance, and long‑term maintainability.
Accountability & execution – reliably follows through on commitments, drives initiatives to completion, and is comfortable being the person ultimately responsible for making the data platform work.
Strong communication skills – can explain technical concepts clearly to non‑technical stakeholders and collaborate effectively with analysts, engineers, and leadership.
Bias toward automation – naturally looks for ways to reduce manual work, standardize processes, and build reusable components.
Attention to detail – cares about data quality, edge cases, and the impact of changes on downstream consumers and clients.
Curiosity and learning orientation – stays current with Azure data services and best practices, and continuously looks for better ways to solve problems.
Collaboration and humility – works well with external consultants and internal teams, and is open to feedback and different perspectives.
Customer focus – understands that better data directly impacts client experience and business outcomes, and prioritizes work accordingly.
Integrity and reliability – can be trusted with sensitive data and production systems, and follows through on commitments.