Data Engineer at VDart Inc — NeverHard

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.