Data Engineering Specialist
AECON View all jobs
- Toronto, ON
- $81,500-95,000 per year
- Permanent
- Full-time
- Safety Always. Our number one core value. If we can't do it safely, we don't do it at all.
- Integrity. We lead by example, with humility and courage.
- Accountability. We're passionate about delivering on our commitments.
- Inclusion. We provide equitable opportunities for everyone.
- Ensure you and your family receive the services needed to support your mental, emotional, and physical well-being.
- Believe in helping you build your career through our Aecon University and Leadership Programs.
- Are committed to supporting and investing in inclusive work environments, through initiatives like Equity, Diversity & Inclusion training, our Aecon Women in Trades and Aecon Diversity in Trades programs, and our Employee Resource Groups (ERGs) to ensure we are building inclusion into every aspect of our culture at Aecon.
- Are a leader in sustainable construction. With a strong commitment to operating responsibly by minimizing our impact on the environment and surrounding communities.
- Develop and maintain robust pipelines for ingesting data from diverse sources, including IoT devices, operational systems, and field applications.
- Ensure data is clean, timely, and reliable for downstream analytics and modeling.
- Build connectors and workflows to integrate with various enterprise platforms and tools.
- Normalize and transform semi-structured, unstructured and nested data into usable formats for analytics and AI/ML applications.
- Support data engineering efforts on the Azure Data Platform (including Azure Databricks, Data Lake, and other services)
- Create workflows to extract insights from documents, images, emails, and other unstructured formats.
- Implement OCR, NLP preprocessing, and metadata extraction pipelines.
- Converting unstructured data to markdown
- CI/CD Automation in Databricks
- Design and implement continuous integration and continuous deployment (CI/CD) workflows within Databricks to streamline code updates, automate testing, and accelerate delivery of data pipelines and analytics solutions. Leverage version control and automated build processes to ensure code quality and reproducibility across environments.
- Collaborate with AI/ML teams to deliver curated datasets with engineered features, labeled examples, and consistent schemas.
- Build feature pipelines, manage dataset versioning, and track data lineage.
- Strengthen system reliability and reduce technical debt by supporting ingestion, integration, and data infrastructure.
- Monitor and optimize performance across data workflows.
- Play a foundational role in enabling AI-driven capabilities such as predictive analytics, anomaly detection, and intelligent automation.
- Ensure the AI/ML team has the data infrastructure needed to deliver high-impact solutions.
- Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
- 3+ years of experience in data engineering, preferably in AI/ML environments.
- 3+ years of experience using Databricks and/or MS Fabric
- Proficiency in Python, SQL, and distributed data frameworks (e.g., Spark, Kafka).
- Experience with cloud platforms (e.g., Azure, AWS, GCP) and orchestration tools (e.g., Airflow, Prefect).
- Strong understanding of data modeling, ETL/ELT processes, and unstructured data workflows.