ETL Data Engineer - HYBRID

Day to Day Responsibilities 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. Design and implement batch and near real‑time data pipelines. Build reusable ingestion frameworks for multiple source systems including Trading platforms, Treasury and finance applications, Core banking systems, and 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. Leverage cloud‑native platforms such as 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 Automate testing, deployment, monitoring, and operational support processes. Basic Qualifications 6+ 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, and data modeling and warehousing concepts. 6+ years of experience with at least one major cloud data platform: Snowflake or Databricks. 6+ years of experience building enterprise‑scale data pipelines and ingestion frameworks. 6+ years of proficiency in SQL, Python, PySpark, and Scala. 6+ years of experience with AWS, Azure, Snowflake, Databricks, Redshift, and Synapse. 6+ years of experience with data engineering tools such as Airflow, dbt, Kafka, Informatica, and Talend. 6+ years of experience in DevOps & Automation: Git, CI/CD, Terraform, Docker, and Kubernetes. 6+ years of experience in data governance: lineages, metadata, data quality, and data reconciliation.

Travel: Hybrid position in Halifax, Nova Scotia – 3 days in the NTT DATA office required. Degree: Bachelor’s in Computer Science or equivalent work experience. NTT DATA is an equal‑opportunity employer.

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. For Pay Transparency information, please click here. #J-18808-Ljbffr