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Designs and builds cloud-native data pipelines and platforms using Python, SQL, dbt, Airflow, and GCP, integrating AI/ML workflows and real-time analytics.
Build and optimize data pipelines on AWS for clients, focusing on automation, Spark, and CI/CD to enable scalable analytics and business insights.
Build and maintain robust data pipelines using SQL, dbt, and cloud data warehouses like Snowflake or BigQuery to make business data accessible and reliable.
Build and maintain robust data models and pipelines using SQL, dbt, and cloud warehouses (Snowflake/BigQuery/Databricks) to power business decisions.
Build and maintain cloud-based data pipelines and modern data platforms for enterprise clients, focusing on Azure Data Factory, Python, and SQL to ensure reliable, high-quality data flows and analytics.
Designs and maintains scalable data pipelines in Python, SQL, dbt, and Airflow, ensuring data quality and governance across BigQuery, Snowflake, and Databricks to support AI-driven workflows.
Designs and builds cloud-based data pipelines and analytics platforms on Microsoft Azure or GCP, using ETL tools, SQL, Python/Java/Scala, and data-lake architectures to deliver business insights.
Design and build efficient data pipelines using BigQuery and Dataflow for a digital transformation consultancy, collaborating with client teams to meet data needs.
Build and maintain scalable ETL/ELT pipelines on Google Cloud Platform, optimize BigQuery warehouses, and automate data workflows with Python, SQL, and Terraform for real-time analytics and business insights.
Build and maintain cloud-based data pipelines in Python and SQL, design modern data platforms (Data Lake, Warehouse), and ensure data quality and observability for analytics and AI projects.
Design and build scalable GCP data pipelines and deploy agentic AI systems using Vertex AI, LangChain, and RAG for enterprise clients.
Build and maintain modern data pipelines and warehouses for ad-tech clients using SQL, Python, BigQuery/Snowflake, and Airflow.
Designs, builds, and optimizes GCP data pipelines using BigQuery, Python, and SQL to support banking analytics in a Scrum team.
Build and maintain large-scale data pipelines and warehouses for a retail-focused analytics platform using GCP BigQuery, SQL, Python, and DevOps practices.
Lead the design and optimization of cloud-based analytics pipelines and data models for a global video platform, using GCP, Airflow, and BigQuery.
Build and maintain data pipelines in Python/PySpark and SQL, working with Hive/Hadoop/Cloudera and Snowflake/BigQuery to support a media-sector client’s data platform.
Build and maintain dbt data models in Snowflake/BigQuery, design layered data architectures, and set up CI/CD pipelines for a 3-month freelance role.
Lead a team to design and build end-to-end data architectures on Google Cloud, using BigQuery, Dataflow, and DBT to create scalable ETL/ELT pipelines and integrate GenAI services.
Design and build scalable cloud data pipelines on Google Cloud Platform (BigQuery, Dataflow, etc.) to enable AI-driven analytics and business intelligence for enterprise clients.
Build and maintain scalable data pipelines, warehouses, and lakes for public-sector or energy clients using Spark, Snowflake, Kafka, and GCP/Azure.
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