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Builds and maintains Databricks Lakehouse data pipelines and AI foundations for clients, designing medallion architectures, Delta Lake tables, and Unity Catalog governance to power analytics and AI-enabled products.
Design and lead enterprise-scale data platforms (Lakehouse, Data Mesh) and ML pipelines using cloud tools (AWS/GCP/Azure), then mentor teams to deliver analytics and data products for ad-tech clients.
Build and maintain scalable data pipelines and analytics solutions for RTX’s enterprise services, integrating diverse data sources and supporting AI/ML initiatives with Python, SQL, and PySpark.
Build and operate production-grade ML platforms on AWS/Azure, turning research prototypes into reliable, scalable systems for global retail brands.
About Deutsche Börse Group: Headquartered in Frankfurt, Germany, Deutsche Börse Group is a leading international exchange organization and market infrastructure provider. They empower investors, financial institutions,…
Build and maintain scalable data pipelines on Databricks using Spark/PySpark to power analytics, reporting, and risk systems for a large North American bank.
Designs and implements enterprise data models and architectures for T-Mobile’s consumer customer success systems, using Snowflake, Databricks, and Kafka to build scalable, real-time data pipelines.
Lead a team of data scientists to build ML models and real-time analytics for IoT and supply-chain solutions, using Databricks and forecasting techniques to optimize Zebra’s products and customer outcomes.
Leads a portfolio of real-estate data platforms and workflow tools, defining strategy, prioritizing features, and mentoring product teams to modernize title and settlement services.
Designs and oversees TaskUs’s cloud-based data platform, choosing compute engines, open-table formats, and tiered storage to keep analytics fast, secure, and cost-efficient for high-concurrency users.
Lead hands-on engineering of an Azure Databricks platform, optimizing Serverless compute, FinOps controls, and migrating POSIT/RStudio workloads to Databricks.
Senior Data Architect designs and implements scalable lakehouse architectures on Databricks and cloud platforms, leading client engagements in data engineering, analytics, and AI initiatives.
Build and optimize Databricks pipelines in Python and SQL to power AI and analytics for enterprise clients, focusing on scalable cloud data solutions.
Designs and owns scalable data platforms for retail and downstream operations, using Databricks, AWS, Azure, Kafka, Airflow, dbt, SQL and Python to deliver governed, business-ready data products.
Build and optimize cloud-scale data pipelines on AWS and Databricks for government clients, focusing on Delta Lake, PySpark, and governed analytics-ready datasets.
Build and maintain ETL pipelines in Informatica and AWS/Databricks, creating Java-based data services and APIs to move and curate enterprise data for analytics.
Design and build Azure Lakehouse architectures with Databricks, ADLS Gen2, Synapse, and Data Factory, and implement scalable ETL/ELT pipelines using Spark, Delta Lake, Python, SQL, and Scala.
Role Overview: We are looking for a skilled and passionate Databricks Engineer to design, build, and optimize enterprise-scale data lakehouse solutions on the Databricks platform. The successful candidate will be…
Build, secure, and automate Databricks on AWS for Vanguard’s fintech platform, provisioning workspaces, Unity Catalog, and AWS infrastructure while enabling AI/ML workloads and enterprise governance.
Build and optimize data pipelines for an auto-insurance cloud platform, using PySpark, Databricks, AWS, and Airflow to process structured, semi-structured, and unstructured data for analytics and AI.
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