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 DevOps .
- 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