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About the Role

The Senior Data Engineer will design, build, and operate Orca’s data ingestion, transformation, and analytics platforms. This role involves end-to-end delivery of ingestion frameworks, data quality controls, and metadata management for freight and shipment data, acting as a technical reference and mentor for junior team members.

Responsibilities

• Design and build metadata-driven ingestion pipelines to onboard new carrier feeds using standardized, reusable patterns.
• Develop and maintain data transformation logic in Microsoft Fabric using T-SQL and Python, ensuring idempotent loads and structured error handling.
• Implement automated data quality controls with alerting integrated to Azure Monitor and Log Analytics.
• Own retention and tiering automation across Azure SQL and SQL Server, including archival and compaction routines.
• Build and maintain metadata catalog and lineage tracking for modernized datasets using Microsoft Purview or equivalent tooling.
• Contribute to large-tenant database strategy work, including performance benchmarking and pilot migration execution.
• Develop reusable transformation and validation libraries that reduce time-to-onboard for new carrier feeds.
• Collaborate with the Data Analysis team to expose modernized data through Fabric semantic models and Power BI datasets.
• Contribute to CI/CD pipelines and Infrastructure-as-Code for data services using Azure DevOps Pipelines, Terraform, and Bicep.
• Act as a mentor to data analysts and future data engineers on pipeline design, data modelling, and quality practices.
• Participate in code reviews and architecture reviews, providing technical feedback.
• Document ingestion patterns, transformation logic, data quality rules, and operational runbooks.
• Support incident response and root-cause analysis for data-service issues, including remediation and post-incident learning.

Requirements

• 5+ years of professional experience as a Data Engineer or similar role, building and operating production data pipelines.
• Post-secondary degree in Computer Science, Software Engineering, Data Engineering, or a related discipline.
• Strong hands-on experience with Microsoft Azure data services: Azure Data Factory, Azure SQL, SQL Server, and Azure Storage.
• Experience with Microsoft Fabric or a comparable modern data platform (Databricks, Snowflake) is required.
• Proficiency in T-SQL and Python for data transformation, orchestration, and scripting.
• Demonstrated experience designing and maintaining metadata-driven ingestion frameworks and reusable transformation libraries.
• Experience implementing data quality controls, schema-drift detection, and observability for data pipelines.
• Exposure to Infrastructure-as-Code (Terraform, Bicep, or ARM) and CI/CD using Azure DevOps Pipelines is required.
• Experience with Power BI semantic models and dataset development is considered an asset.
• Prior experience with EDI, SFTP-based data exchange, or freight/logistics data is considered an asset.
• Prior experience with Microsoft Purview or equivalent catalog and lineage tooling is a plus.
• Strong communication skills; comfortable engaging both technical and business audiences with clarity.
• Comfortable with ambiguity and greenfield problem-solving; able to define patterns where none exist yet.
• Ownership mindset; sees a system through from design to production operation.
• Mentoring orientation; willing to invest time in growing junior team members’ capability.
• Resilient in a high-autonomy environment with limited established process today.

Skills

• Microsoft Fabric
• Azure Data Factory
• Azure SQL
• SQL Server
• Power BI
• Python
• T-SQL
• Microsoft Purview
• Azure Monitor
• Log Analytics
• Azure DevOps Pipelines
• Terraform
• Bicep
• EDI
• SFTP

Experience Level

• Senior

Education Level

• Post-secondary degree in Computer Science, Software Engineering, Data Engineering, or a related discipline

About the Company

• Orca’s data function scales