Design and implement scalable ETL/ELT pipelines on modern cloud data platforms - AWS (Glue, Step Functions, Lambda, S3), Databricks, Spark or Microsoft Fabric.
Lead data platform architecture & design — design enterprise data lakes, warehouse schemas, and ETL frameworks for mission-critical banking and financial systems
Work closely with internal stakeholders to understand their reporting needs, conduct analysis and share actionable insights to support data-driven business decisions
Understand the business model, customer journey, operational constraints, and drivers of revenue, margin, cost, retention, and risk; identify where better decisions will create the most value.
Understand the business model, customer journey, operational constraints, and drivers of revenue, margin, cost, retention, and risk; identify where better decisions will create the most value.
We are seeking an experienced Teradata Data Architect to design and lead enterprise-scale data architecture, data warehousing, and Lakehouse solutions. The ideal candidate will have strong expertise in Teradata, modern Databricks architecture, data modelling, and large-scale data processing using PySpark. The role involves modernizing legacy data platforms, implementing scalable Lakehouse architectures, and establishing enterprise data governance and security standards.
Our data ecosystem will be migrating their products from Azure to AWS. Data Engineers needed to assist with new and current pipelines. All IT equipment are provided and it is the responsibilities of consultants to ensure the security of the organization's data and applications.