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Design and maintain scalable data pipelines and platforms using Databricks, PySpark, and cloud ecosystems for enterprise clients across multiple industries.
Build and maintain scalable data systems, design ETL/ELT pipelines, and optimize data quality using AWS, Python, SQL, and Spark for analytics and ML workloads.
Designs and maintains scalable data pipelines and cloud-based data warehouses to feed analytics and AI models, using Python, Spark, Kafka, and cloud platforms like AWS/Azure/GCP.
Build and maintain data pipelines and infrastructure for a fast-growing multi-currency fintech wallet, enabling analytics, AI agents, and customer-facing features across APAC markets.
Lead the design and delivery of scalable data platforms and analytics solutions using Databricks, Snowflake, and Tableau to enable self-service BI and advanced analytics across Finance, Supply Chain, and other domains.
Build and maintain ETL/ELT pipelines and data integration solutions using SQL, Python, and cloud tools like AWS Glue and Lambda.
Build and maintain scalable data pipelines in Databricks/Snowflake, ingest external financial data, and enforce data quality and governance for a fintech platform.
Lead the design and build of a risk/analytics data platform for an investment firm, owning pipelines, governance, and stakeholder alignment.
Design and build modern data analytics, Big Data, and data-warehouse solutions in AWS, GCP, or Azure, including ETL/ELT pipelines and governance using Databricks, Snowflake, and Spark.
Designs and builds secure, scalable GCP data pipelines (batch/streaming) using BigQuery, Dataflow, and Scala/Java/Python to turn raw data into business insights.
Build and optimize cloud-native data pipelines on Azure, migrating and transforming data for analytics and ML workloads using Spark, Databricks, and Azure Synapse.
Build and maintain Azure Databricks pipelines and data models that power financial insights for global wind projects, collaborating with finance teams to deliver scalable data solutions.
Designs, builds, and scales GCP-based data pipelines and warehouses, implementing ETL/ELT, real-time streaming, and big-data architectures while collaborating with analytics and business teams.
Build and scale AI-optimized data pipelines, transform unstructured data into vectorized formats, and maintain real-time feature stores for LLM and ML workloads.
Builds and maintains cloud data pipelines using Azure Databricks, PySpark, and Delta Lake to power analytics and BI in a modern Lakehouse architecture.
Builds and optimizes BI data models, ETL/ELT pipelines, and dashboards in Power BI/Qlik Sense to standardize reporting across European markets using SQL, Snowflake, ADF, and dbt.
Build and maintain scalable data pipelines on GCP using Python, Airflow, Spark, and BigQuery to power analytics and decision-making.
Senior AI Data Engineer builds and maintains scalable ELT pipelines and dbt models for Zendesk’s analytics platform, integrating AI tools to enhance data delivery and team productivity.
Senior Data Engineer designs and builds enterprise data platforms, ELT pipelines, and AI-ready architectures to power analytics and machine learning at a global tobacco-alternative company.
Build and maintain cloud-based data pipelines and transformations using GCP, Python, and SQL to turn raw data into business insights for enterprise clients.
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