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Build and maintain high-volume data pipelines on AWS/Snowflake, transforming raw ingestions into clean, modeled datasets for analytics and reporting.
Build and maintain scalable data pipelines and warehouses for an online DIY/home-improvement marketplace using Snowflake, Airflow, Python, Kafka, and S3.
Build and maintain data pipelines, clean and model customer data, and deploy scalable BigData solutions on AWS/Azure for marketing analytics.
Build and maintain robust data pipelines and ETL workflows for a public-sector client using Talend/Informatica, Airflow, and modern data platforms like Trino and Iceberg.
Build and maintain data pipelines and transformations for a SaaS platform serving automotive manufacturers and dealers, using dbt, Python, SQL, AWS S3/Redshift, and Parquet.
Build and maintain a scalable, multi-tenant data warehouse for a healthcare group, using S3, Iceberg, Trino, and Spark while securing IAM flows with Keycloak.
Build and maintain data pipelines and transformations for a mobility-focused platform, using AWS S3, dbt, and Redshift to feed analytics and business solutions.
Build and optimize end-to-end data pipelines on Databricks and Spark, handling ingestion, modeling, storage, and exposure while mentoring peers and running DevOps practices.
Data Engineer building and maintaining a large-scale data platform for a major bank, automating data ingestion and ensuring quality in a high-volume environment.
Build and optimize data pipelines for a fintech’s Data Lake using Snowflake, DBT, Pulumi, AWS, and Python, then deliver analytics via Power BI.
Build and maintain data pipelines, ETL processes, and BI dashboards using Python, GCP/AWS, and Power BI to support business analytics and reporting.
Build and optimize large-scale data pipelines and distributed systems using Spark, Databricks, and AWS to power AI-driven B2B intelligence products.
Build and maintain data pipelines in Python and SQL, orchestrating ETL/ELT workflows with Apache Airflow on AWS to feed AI models and internal analytics tools.
Design and build scalable data pipelines and cloud-based data platforms using PySpark, Snowflake, and Databricks to support AI and analytics initiatives.
Senior Data Engineer builds and maintains Matillion ELT pipelines feeding Snowflake, transforming raw data into analytics-ready models across multi-layer data architecture.
Build and maintain scalable data pipelines for an e-commerce platform using Snowflake, Airflow, Python, S3, and Kafka to ensure reliable, high-quality data flows.
Build and maintain scalable data pipelines and architectures for enterprise clients, using Python, Spark, Airflow, and cloud storage to enable data-driven decision-making.
Lead a team to design and build scalable data pipelines and platforms for clients, advising on cloud and big-data tech while enforcing DevOps, FinOps, and governance best practices.
Build and maintain scalable data pipelines and warehouses for analytics, using cloud tools like AWS and Snowflake, orchestration platforms such as Airflow, and data modeling best practices.
Builds and optimizes scalable data pipelines for a Madrid-based bank, using Spark, Scala, Python, Airflow, and cloud migration from Hadoop.
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