Data Engineer

Requirements:

• 5+ years of experience as a Data Engineer, Data Integration Developer, or similar role.
• Must have hands-on experience with Databricks, including building and supporting production-grade data pipelines.
• Strong experience with Spark/PySpark, SQL, ETL/ELT development, data ingestion, transformation, and pipeline orchestration.
• Experience with Azure data services, including Azure Data Factory, Azure Data Lake Storage, and cloud-based data integration patterns.
• Good understanding of data lakehouse concepts, data modelling, data quality controls, metadata management, and secure data handling.
• Experience with production support, monitoring, troubleshooting, performance tuning, and operational resiliency for data pipelines.
• Ability to manage relationships with technology, data governance, and business partners.
• Advanced verbal and written communication skills, with the ability to explain data engineering concepts clearly to technical and non-technical stakeholders.

Good to Have:

• Experience with Delta Lake, medallion architecture, streaming data, API-based ingestion, Kafka, Autosys, GitHub, CI/CD, or DevOps practices.
• Exposure to legacy data platforms such as Netezza, Oracle, PL/SQL, or Informatica is an asset.