Senior Data Engineer

Requirements

• Bachelor's degree in Computer Science, Statistics, Information Management, or related field
• 6+ years of professional experience in data engineering, data modeling, or related disciplines
• 5+ years designing conceptual, logical, and physical data models with strong expertise in 3NF normalization and dimensional modeling
• Experience applying Inmon and Kimball methodologies; ability to design business keys, surrogate keys, and Slowly Changing Dimensions (SCD)
• Hands-on experience building production data pipelines on modern cloud platforms such as Databricks, Snowflake, BigQuery, or Synapse
• Strong proficiency in Python, PySpark, and SQL for large-scale data transformation
• Experience with medallion or multi-layered data architectures, streaming ingestion, change data capture (CDC), and incremental load strategies
• Familiarity with CI/CD practices, automated deployment pipelines, and infrastructure-as-code concepts
• Strong written and verbal communication skills; ability to convey technical concepts to non-technical stakeholders
• Databricks Data Engineer or Microsoft Azure Data Engineer certification is an asset
• Experience with Unity Catalog, Data Vault 2.0, metadata-driven pipeline frameworks, or AI-assisted development tools is an asset
• Work Environment
• Hybrid work model - home and office based
• Travel required on occasion (

Benefits

Additional Information

Ledcor is hiring a Senior Data Engineer to join our Data & Analytics Platform team. In this role, you will design, build, and maintain enterprise-scale data solutions that support reporting, analytics, and operational intelligence across Ledcor's construction and infrastructure businesses. Reporting to the Senior Manager, Data & Analytics Platform, you will work across the full data lifecycle-from source system ingestion and enterprise data modeling through to analytics delivery and governance. You will require deep expertise in data engineering and data modeling, and you will apply that knowledge across a modern Azure Databricks and Delta Lake platform using a medallion architecture approach. You will partner closely with report developers, business analysts, project stakeholders, and platform administrators to ensure trusted, secure, and scalable data solutions are delivered across the organization. Come and join the True Blue team and apply today! Essential Responsibilities Design, build, and maintain production-grade data pipelines using PySpark and Databricks Spark Declarative Pipelines (SDP), including Python and SQL transformations across medallion architecture layers Configure and contribute to metadata-driven ingestion processes using YAML-based configurations and code generation frameworks that automate pipeline creation Support infrastructure-as-code deployments using Databricks Asset Bundles (DAB) and implement data quality expectations and monitoring throughout pipeline stages Design conceptual, logical, and physical data models using Information Engineering (crows-foot) notation, applying Inmon, Kimball, and Data Vault methodologies as appropriate Build and maintain normalized enterprise data structures and dimensional analytics models, including business key and surrogate key strategies, SCD patterns, and referential integrity standards Contribute to enterprise modeling standards, naming conventions, and data governance practices Implement row-level and column-level security policies using Unity Catalog; configure role-based and attribute-based access controls, data classification, and governance metadata Define and enforce automated data quality checks across pipelines; develop validation, regression, and reconciliation testing processes between source and target systems Contribute to team testing standards and deployment validation practices

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