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Design and maintain compliant data pipelines for AI productivity tools, focusing on data masking, anonymization, and regional regulatory adherence.
Architect and build a Snowflake/Azure-based enterprise data platform, owning pipelines, modeling, governance, and observability with SQLMesh, Terraform, and GitHub Actions.
Design and maintain large-scale data platforms, metadata systems, and semantic models for enterprise clients using Python, SQL, and modern data stack tools.
Data Analyst focused on strategy and governance, building data catalogs, ensuring quality, and modeling enterprise data assets using T-SQL, Microsoft Fabric, and Power BI.
Build and maintain data pipelines in Dataiku, create Power BI dashboards for wealth portfolio insights, and mentor junior analysts in a fintech setting.
Build and maintain enterprise data ontologies and semantic models to standardize business concepts like Product and Customer across systems, enabling consistent AI, reporting, and governance at IFF.
At USAble Life, we’re committed to making a meaningful difference in the lives of our customers, our communities, and each other. We are a diverse team united by a shared drive to go the extra mile. Through our DEI…
Build and maintain scalable data pipelines and platforms for AML and payments in banking, using Python, Spark, Snowflake, and Azure to process and transform financial data for analytics and compliance.
Build and maintain ETL pipelines and data models for a Canadian bank’s personal-banking analytics, using Azure, Databricks, PySpark, Python, and SQL.
Build and optimize scalable ETL/ELT pipelines for a wealth-tech platform using Snowflake, AWS, and Python, ensuring data quality and governance in a financial-services environment.
Build and own scalable ETL/ELT pipelines and analytics layers in a modern data stack, transforming raw data into reliable insights for business decisions.
Build and maintain data pipelines, models, and ETL jobs in Azure using Python, Delta Lake, and SQL to support banking analytics and reporting.
Design and maintain data pipelines, ETL processes, and cloud-based data solutions to ensure accurate, accessible data for analytics and reporting in an enterprise environment.
Build and maintain data pipelines in Snowflake, SQL Server, and PostgreSQL to feed analytics and reporting for an insurer’s underwriting, claims, and policy systems.
Build and optimize Snowflake-based data pipelines and analytics platforms for fintech clients, using Snowpark, dbt, and FastAPI to deliver secure, scalable data products.
Migrate legacy banking data to new enterprise data marts using SQL, Hive, Impala, and Oozie, then validate and automate reports.
Designs and maintains AWS-based data pipelines and dimensional models to power business analytics and reporting for enterprise clients.
Designs and builds scalable AWS-based ETL/ELT pipelines and data models for product margin reporting, ensuring data quality and lineage.
Lead the design and deployment of enterprise-scale data pipelines and AI solutions on Databricks, building Lakehouse architectures and automating agentic AI workflows for clients.
Lead a team to design and deploy Databricks-based data pipelines and Lakehouse architectures, using PySpark/SQL and cloud platforms to build AI-ready data platforms for enterprise clients.
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