Location: Toronto, ON Work Arrangement: Onsite / 4 Days in Office Salary: $150K–$180K Experience: 12–18 Years We are looking for a Principal Data Engineer – Databricks to lead enterprise-scale data modernization initiatives, with a robust focus on Cloudera-to-Databricks migration, Lakehouse architecture, finance/risk data, and large-scale data engineering .

Key Responsibilities & Requirements 12–18 years of overall data engineering experience. 8+ years of experience with enterprise Data Warehouse and Data Lake platforms . 5+ years of hands-on experience with Databricks and Spark at scale .

Lead modernization of legacy Cloudera platforms (CDH/CDP, Hive, HBase, Impala, Spark) to Databricks Lakehouse.

Redesign ingestion, transformation, and consumption patterns from HDFS-based architecture to cloud object storage and Delta Lake.

Refactor legacy Hive/Impala logic into PySpark and Spark SQL ELT pipelines.

Design and govern enterprise Data Warehouse, Data Lake, and Lakehouse architectures .

Implement Medallion Architecture (Bronze, Silver, Gold) and layered data platforms.

Develop and optimize large-scale pipelines using PySpark, Spark SQL, Delta Lake, and Databricks SQL .

Optimize workloads using Z-ORDER, OPTIMIZE, caching, and cluster configurations .

Build semantic and consumption layers for BI, reporting,



and analytics.

Work with finance and risk data models, including General Ledger, Sub-ledger, financial hierarchies, and credit/liquidity/market risk exposure models .

Support reporting capabilities including aggregation, drill-down, and drill-back.

Implement data governance, data quality, reconciliation, lineage, metadata, security, and compliance controls.

Work with AWS or Azure cloud platforms.

Implement CI/CD using Git, Terraform, Jenkins, or Azure Dev

Ops .

Use orchestration tools such as Airflow or Databricks Workflows .

Experience with dbt is an asset.

Act as a technical authority, lead architecture decisions, mentor senior engineers, and establish engineering standards.

Partner with finance, risk, analytics, and governance stakeholders to deliver business-ready data solutions.

Nice to Have Experience in BFSI, Capital Markets, or regulatory reporting .

Exposure to SAP Finance, Oracle Financials, or S/4HANA .

Experience supporting AI/ML workloads .

Databricks or cloud certifications.

Impact Lead Cloudera-to-Databricks transformation initiatives.

Shape enterprise finance and risk data platforms .

Support regulatory, management, and analytical reporting systems.

📌 Principal Data Engineer – Databricks (Toronto)
🏢 Staffmax Staffing & Recruiting
📍 Toronto