Design and develop modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory. Integrate multiple data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
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Design and develop modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory. Integrate diverse data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
Design and develop modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory. Integrate diverse data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
Design and develop modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory. Integrate diverse data sources into analytical layers while maintaining and evolving existing SQL Server-based data warehouse environments.
Design and develop modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory. Integrate diverse data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
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Design and develop modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory. Integrate multiple data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
Design and develop modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory. Integrate diverse data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
Design, develop, and maintain modern data pipelines and Lakehouse architectures using Azure Databricks and Azure Data Factory. Integrate diverse data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
Design, develop, and maintain modern data pipelines and Lakehouse architectures using Azure Databricks and Azure Data Factory. Integrate diverse data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
Design and develop modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory. Integrate multiple data sources into analytical layers while evolving existing SQL Server environments toward scalable cloud architectures.
Own the end-to-end delivery of AI-automated data platform migration projects, including scoping, planning, and execution. Serve as the primary customer contact to manage expectations and partner with engineering teams to refine the delivery playbook.
Architect and implement enterprise-grade GenAI data platforms for the ingestion and processing of structured and unstructured data. Design scalable pipelines for knowledge preparation, including chunking, embeddings, and serving AI-ready data models.
Design, build, and maintain scalable data pipelines and cloud-based architectures to support federal government programs. Collaborate with cross-functional teams to integrate diverse data sources and ensure compliance with federal security requirements.
Build and ship production-quality data normalization, schema mapping, and enrichment pipelines for a new AI-native data warehouse. Collaborate with Staff engineers on technical architecture and implement AI-accelerated development practices.
Design and implement the core components of an AI-native data platform, including schema mapping, normalization, and distribution pipelines. Establish technical standards and build evaluation infrastructure to ensure the reliability of AI-generated financial data.
Architect complex systems and make critical technical decisions while mentoring engineers and promoting engineering excellence across teams. Align technical strategies with business goals through cross-functional collaboration and contribute to technical roadmaps and strategic planning.
Lead the development and management of the data platform, focusing on foundational data models and scalable data solutions for cross-border remittances. Oversee the entire build and deployment lifecycle, ensuring robust data governance and efficient resource allocation.
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Lead the development of domain data products, including batch, streaming, and AI/ML feature pipelines. Partner cross-functionally to design scalable data solutions and ensure data reliability, governance, and performance.
Build and maintain data pipelines for collecting, transforming, and integrating data from various sources. Ensure efficient data enablement and reporting solutions through the deployment of scalable data products.
Design and implement scalable, domain-oriented data pipelines on AWS to support analytics and business-critical workflows. Collaborate with cross-functional teams to ensure data quality, reliability, and performance across various data domains.
Design and implement scalable, domain-oriented data pipelines on AWS to power analytics and business-critical workflows. Collaborate with cross-functional teams to optimize data quality, reliability, and performance across various data domains.
Build and maintain highly available, scalable data infrastructure and ETL pipelines to process petabytes of blockchain transaction data. Collaborate with cross-functional teams to design intricate data models that support sub-second query latency for security products.
Design and maintain scalable data infrastructure, including ETL pipelines and real-time streaming solutions. Ensure data quality, governance, and performance optimization to support strategic business decision-making.
Design, implement, and optimize modern data architectures using Big Data technologies, specifically focusing on data lakes and lakehouses. You will be responsible for collecting, cleaning, and orchestrating large volumes of structured and semi-structured data to drive business decision-making.
Design and implement scalable data pipelines and ETL/ELT processes using GCP services like Dataflow and BigQuery. Collaborate with clients to translate business needs into technical data solutions while optimizing performance and costs.
Design, build, and maintain scalable data pipelines and cloud-based architectures to support federal government programs. Collaborate with cross-functional teams to integrate diverse data sources and ensure compliance with federal security requirements.
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Design and maintain scalable data pipelines and analytical data models to power clinical operations and AI initiatives. Collaborate across teams to build dashboards and contribute backend application code for data-intensive features.
Define and drive the organizational strategy for data reliability, quality, and operational excellence. Lead the design of scalable observability frameworks and establish company-wide standards for data contracts and governance.
Lead the design and development of scalable data processing and persistence components within agile teams. Provide technical leadership, enforce development best practices, and manage the performance and career growth of junior staff.
Design and develop large-scale data processing and persistence software components within agile teams. Provide technical leadership, mentor team members, and ensure software meets non-functional requirements and operational readiness.
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