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Build and optimize data pipelines (ETL/ELT) in Azure to integrate and clean hotel and guest data, enabling analytics and Power BI dashboards for business decisions.
Build and optimize scalable ETL/ELT pipelines, populate data warehouses and lakes, and secure tenant data for AI-powered analytics across Emburse’s products.
Build and optimize scalable, multi-cloud data pipelines using SQL, Python, and ETL/ELT tools while collaborating with clients and internal teams.
Build and maintain cloud data pipelines on GCP and Databricks, using BigQuery, Airflow, dbt, and Dataflow to feed dashboards and experiments.
Build and maintain AWS-based data pipelines that ingest and transform structured data into Redshift using PySpark, SQL, and ETL/ELT tools.
Build and maintain Azure-based data pipelines for a financial data platform, implementing ETL/ELT patterns and ensuring data governance.
Designs and scales high-performance ELT pipelines and data platforms using SQL and Python to improve data quality and performance.
Designs and builds scalable data pipelines on GCP for a capital-markets fintech, integrating financial data sources and optimizing warehouse/lake solutions.
Build and optimize Azure-based data pipelines and ETL workflows using Synapse, PySpark, and Databricks to ingest and process large-scale datasets.
Designs and builds GCP-based ETL/ELT pipelines and data governance workflows using BigQuery, Dataflow, Airflow, and related tools.
Designs and builds cloud data pipelines and architectures using SQL, Python/Scala, and Spark to process and optimize ETL/ELT workflows in a hybrid environment.
Builds and maintains scalable data platforms for a bank’s transformation using Python, SQL, and cloud tools, collaborating with senior engineers.
Build and deploy AI agents and automation pipelines in Python to streamline supply-chain compliance workflows for life-sciences companies, using dbt, Docker, and cloud platforms.
Senior Data Engineer builds and maintains scalable ETL pipelines using Python, Snowflake, and Azure, focusing on cloud data warehousing and dimensional modeling.
Lead a team of trainees to build scalable GCP-based data pipelines using BigQuery, Airflow, and Dataflow, while mentoring junior engineers and enforcing data governance standards.
Build and maintain modern data platforms (lakehouse, data warehouse) and ETL/ELT pipelines in cloud and on-prem, integrating structured and unstructured sources to enable analytics and AI solutions.
Build and scale Snowflake-based data and AI systems, designing pipelines, models, and LLM/RAG applications that turn messy business data into trusted, production-ready solutions.
Build and maintain scalable data pipelines and ETL/ELT workflows using SQL and Python to support analytics and reporting in a hybrid work environment.
Data Engineer builds and maintains cloud-based data pipelines and ETL/ELT workflows for production systems, collaborating with data scientists and architects to deliver scalable, high-quality solutions.
Build and maintain data pipelines, warehouses, and dashboards for a Peruvian tech distributor, integrating SQL, SAP HANA, and PostgreSQL sources to deliver trusted analytics for business decisions.
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