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Builds and governs data platforms (Data Lake, Lakehouse, Data Mesh) and ensures data quality, compliance, and security while collaborating with teams to meet business data needs.
Acts as the technical lead for Databricks’ Data & AI platform post-sale, driving customer adoption and growth by aligning stakeholders, resolving escalations, and coordinating internal teams to maximize platform ROI.
Lead the design and implementation of a modern cloud data ecosystem, including a lakehouse architecture and scalable AI/ML capabilities for an enterprise.
Lead enterprise data and AI strategy, designing scalable data ecosystems and cloud-native platforms while guiding AI/ML initiatives and governance for digital innovation.
Build and maintain cloud-based data pipelines and warehouses using Python, SQL, and tools like GCP, Azure, Snowflake, and dbt to support BI and AI systems.
Build and maintain a cloud-based lakehouse data architecture for Aon’s Commercial Risk Solutions, designing scalable ETL pipelines and ensuring data quality for analytics.
Senior data analyst builds dashboards in Power BI, writes advanced SQL on Databricks, and delivers insights to guide business decisions across teams.
Designs and maintains enterprise data architecture, builds scalable data platforms (lakes, warehouses, streaming), and sets standards for modeling, governance, and cloud integration to support analytics and AI.
Designs and builds scalable data pipelines and modern data warehouses using Microsoft Fabric, Azure, and Databricks to enable analytics and reporting.
Designs and builds end-to-end data pipelines on Azure Synapse and Data Factory, modeling relational/ dimensional data in T-SQL and PySpark to deliver governed analytics platforms for clients in industrial, energy, consumer and public sectors.
Build and maintain a Lakehouse platform using PySpark and Databricks, designing Delta Lake schemas and batch/near-real-time pipelines for reliable, scalable data solutions.
Build and maintain a PySpark and Delta Lake-based data lakehouse on Databricks, creating batch and near-real-time pipelines to power analytics and data sharing for internal products.
Build and maintain scalable ETL/ELT pipelines and lakehouse architectures, design data models, and collaborate with ML/AI teams in a hybrid setup.
Build and maintain Snowflake and AWS-based data platforms, automate infrastructure with Terraform, and run secure data pipelines across 60+ countries.
Own and evolve a Snowflake-based data platform and AWS lakehouse, managing Terraform infrastructure and Airflow workflows in a hybrid Barcelona role.
Designs and builds data pipelines and warehouses for clients using Hadoop, Snowflake, Kafka, Spark, and Python/Java.
Builds and maintains data ingestion pipelines, lakehouse environments, and real-time streaming systems using SQL, PySpark, Kafka/Kinesis, and Go.
Builds and maintains PySpark pipelines on Databricks to power reliable data products and enrichment workflows for a SaaS analytics platform.
Design and build scalable data platforms, lakehouse architectures, and ETL/ELT pipelines while collaborating with ML/AI teams to shape data strategy.
Build streaming and batch data pipelines, govern schemas, and create self-serve tools for trading, wealth, and product teams using a lakehouse and time-series layer.
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