Data Engineer

Role: Data Engineer

Location: Halifax Nova Scotia(Hybrid)

Type: Contract

Day to Day job Duties:

• Cloud Data Warehousing & Engineering
• Design develop and maintain enterprise cloud data warehouse solutions supporting business risk finance and regulatory reporting needs.
• Build scalable and resilient data ingestion transformation and orchestration pipelines using cloud-native technologies.
• Develop and optimize ETL/ELT frameworks for structured semi-structured and streaming datasets.
• Enable enterprise reporting and analytics by delivering curated governed and trusted datasets.

Data Pipeline Development:

Design and implement batch and near real-time data pipelines.

Build reusable ingestion frameworks for multiple source systems including:

Trading platforms:

• Risk systems
• Treasury and finance applications
• Core banking systems
• Market and reference data platforms
• Implement metadata-driven and configurable pipeline architectures.

Data Modeling & Warehousing:

• Design and implement dimensional models star schemas snowflake schemas and curated data marts.
• Support enterprise data warehouse optimization partitioning clustering and performance tuning.
• Build semantic and consumption-ready datasets for downstream analytics and reporting.

Cloud Platform Engineering:

• Develop solutions leveraging cloud-native platforms such as:
• AWS / Azure / GCP
• Snowflake / Databricks
• Cloud storage and compute services
• Implement scalable processing frameworks and distributed compute patterns.

Data Quality Governance & Security:

• Implement data quality checks reconciliation controls lineage and observability frameworks.
• Ensure compliance with banking regulatory security and governance requirements.
• Support enterprise metadata management and lineage tracking.
• Apply secure access models and data masking standards for sensitive financial data.

Performance Optimization:

• Optimize warehouse performance compute utilization and storage costs.
• Improve query performance data refresh SLAs and pipeline reliability.
• Implement partitioning indexing clustering and workload optimization techniques.

DevOps & Automation:

• Build CI/CD pipelines for data engineering deployments.
• Automate testing deployment monitoring and operational support processes.
• Basic Qualifications: (what are the skills required tthis job with minimum years of experience on each)
• Seeking a Data Engineer tjoin the Cloud Data Warehousing team responsible for building scalable secure and high-performance enterprise data platforms in the cloud. This role will focus on designing and implementing modern cloud-native data pipelines data warehousing solutions and ingestion frameworks that enable analytics regulatory reporting risk management finance and business intelligence capabilities across the enterprise.
• 6 10 years of overall experience in data engineering data warehousing or cloud data platform development.
• 6 Years of Strong hands-on experience in:
• SQL (advanced)
• Python / Spark / Scala
• ETL/ELT frameworks
• Data modeling and warehousing concepts
• 6 Years of Experience with at least one major cloud data platform:
• Snowflake
• Databricks
• 6 Years of Experience building enterprise-scale data pipelines and ingestion frameworks.
• Strong understanding of data warehouse architecture patterns.
• 6 Years of Languages & Processing: SQL Python PySpark Scala
• 6 Years of Cloud & Warehousing: AWS Azure Snowflake Databricks Redshift Synapse
• 6 Years of Data Engineering Tools: Airflow dbt Kafka Informatica Talend
• 6 Years of DevOps & Automation: Git CI/CD Terraform Docker Kubernetes
• 6 Years of Data Governance: Lineage Metadata Data Quality Data Reconciliation
• Travel: Hybrid Position in Halifax Nova Scotia Canada (3 days in Client office)
• Degree: Bachelors in Computer Science or equivalent work experience

Nice tHave:

• The ideal candidate will have strong expertise in cloud data platforms ETL/ELT engineering data modeling and enterprise data integration with experience working in regulated financial services environments. The role requires close collaboration with architecture analytics risk finance operations and application teams tmodernize enterprise data ecosystem
• Experience in Banking / Financial Services / Capital Markets.
• Experience with:
• Airflow / Control-M / cloud orchestration
• Kafka or streaming platforms
• Terraform / CloudFormation
• GitHub Actions / Jenkins / CI-CD tools
• Exposure tlakehouse and modern data mesh architectures.