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Finance Database Engineer building and maintaining scalable data pipelines, SQL data models, and Power BI dashboards on Microsoft Azure and Microsoft Fabric to support financial reporting and operations.
Build and maintain data pipelines for fintech analytics and reporting, ensuring reliable data access for high-impact decisions.
Data Engineer building and maintaining real-time and batch data pipelines for financial analytics and payments within an iGaming company's fintech ecosystem, using SQL, ETL/ELT workflows, and streaming platforms like Kafka.
Data Architect owning data architecture on a Snowflake-based global data platform for a global entertainments business, defining models, data contracts and standards to support pricing, marketing measurement and forecasting decisions.
The Senior Database Architect will lead the modernization of legacy SQL Server stored procedures while designing AI-native data infrastructure, including vector databases and semantic models. The role involves leveraging AI tools to automate database refactoring and building scalable data platforms to support AI agents and workflows.
Senior Azure Data Engineer with 5+ years experience designing scalable data solutions on Microsoft Azure using tools like Azure Data Factory, Databricks, and Synapse.
Data Engineer building scalable data pipelines, ETL/ELT processes, and cloud-based data architectures (Data Warehouse, Data Lake, Lakehouse) on AWS using SQL, Python/Scala, Spark, Airflow/dbt.
Senior Developer in Data Engineering role focusing on data stack modernization, migrating from traditional ETL tools to cloud-native ELT stack using AWS, Python, Airflow, DBT, and Snowflake. Responsible for data modeling, data quality, and building scalable data pipelines.
Senior Data Engineer builds scalable pipelines and systems to productionalize predictive models for Carvana’s automotive retail platform, using Python, Docker/Kubernetes, and cloud services.
Senior Data Engineer on a 6-month hybrid contract modernizing the data stack, migrating from ETL tools to a cloud-native ELT pipeline on AWS using Python, Airflow, DBT, and Snowflake.
Build and deploy AI/ML solutions end-to-end: design MLOps pipelines, automate cloud infrastructure, and operationalize models in production using Python, Docker, and cloud platforms.
Senior Data Engineer at Scotiabank in Toronto designing, building, and maintaining scalable data pipelines and cloud data platforms using Azure, Databricks, and SQL/Python/Java/Scala, while leading a team of engineers.
Leads enterprise data governance programs, consulting, and Databricks practice development for a consulting firm, designing frameworks, policies, and client solutions for data stewardship, quality, and metadata management.
Customer Data Analyst building dashboards and bespoke analyses for utility grid customers using SQL, Python, Databricks, dbt, and AWS in a startup environment.
Migrates legacy AS400/DB2 data to PostgreSQL and builds Odoo integrations, ETL pipelines, and reporting datasets for a LATAM client’s AWS-hosted ERP modernization.
Data Engineer designing and maintaining Azure-based ELT pipelines and data platforms, collaborating on data extraction, transformation, and loading into a data warehouse with a focus on data quality, governance, and automation in a hybrid setup.
Lead Data Engineer designing and delivering scalable data architectures, pipelines, and models using Azure Databricks, dbt, and SQL while mentoring engineers and enforcing CI/CD and data quality best practices.
Lead Data Engineer at Novare in the Philippines designing scalable data architectures with Azure Databricks, dbt, and SQL, leading ELT/ETL workflows, and mentoring a team of engineers.
Data Engineer responsible for designing, developing, and maintaining ETL/ELT pipelines and data architecture on Microsoft Azure, including Databricks, ADLS Gen2, ADF, and Synapse, while ensuring data governance and quality.
Data Engineer at NNIT's AI Center of Excellence designing and building enterprise cloud data platforms—ETL/ELT pipelines, data lakes, and lakehouses—using Azure, Databricks, Snowflake, Python, and SQL to enable AI and analytics for global clients.
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