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Builds and optimizes GCP-based data pipelines using BigQuery, Cloud Functions, and Airflow to process large datasets and integrate APIs for analytics and reporting.
Build and optimize data pipelines on GCP, focusing on BigQuery performance, serverless data flows, and data governance while using Python, SQL, and DevOps practices.
Build and maintain scalable dbt data models and migrate dashboards to Looker to deliver trusted business insights in a fintech environment.
Build and maintain Bolt’s data platform, enabling teams to create reliable, self-service data products using Python, dbt, Databricks, Airflow, and Kubernetes at petabyte scale.
Builds and optimizes ad-tech and AI-driven data products, analyzing large datasets to improve targeting and business decisions using Python, SQL, and visualization tools.
Builds data-driven ad-tech and AI products by analyzing large datasets, writing Python/SQL queries, and creating dashboards to optimize marketing campaigns for global brands.
Build and maintain data pipelines and a BigQuery-based data warehouse for a global ride-hailing platform, reconciling financial data from multiple providers.
Senior engineer designs and implements GCP-based data governance, metadata catalogs, and data quality processes for a Telco client migrating analytics to the cloud.
Builds and optimizes data models in PySpark/SQL to support scalable analytics and dashboards, collaborating with business stakeholders and engineers to turn marketing, sales and logistics data into actionable insights.
Build and maintain cloud-based data pipelines and AI solutions for public-sector clients using Python, SQL, DBT, and Looker.
Design and build scalable Lakehouse architectures (Bronze/Silver/Gold) using Databricks and Delta Lake to transform logistics data into BI insights, optimizing ETL/ELT pipelines with PySpark and Azure/AWS/GCP services.
Build and maintain scalable Azure data pipelines and lakehouse solutions using Databricks, PySpark, and Azure Data Factory to process and transform large datasets for enterprise clients.
Build and maintain scalable Azure data pipelines and Databricks lakehouse solutions, transforming raw data into analytics-ready assets while collaborating with cross-functional teams.
Build and maintain scalable data pipelines for large enterprises using Spark, Cloudera, and Airflow to process streaming and batch automotive, aerospace, and telecom data.
Senior Data Engineer designs and builds scalable data pipelines and warehouses, mentors junior engineers, and ensures reliable data delivery for analytics and business insights.
Designs and builds GCP-based data pipelines, warehouses, and storage systems using BigQuery, Airflow, and Python; troubleshoots performance issues and mentors junior engineers.
Build and optimize GCP-based data pipelines and ML models, then visualize insights in Looker Studio to drive TELUS’s operational and customer-experience improvements.
Build and maintain data pipelines, ETL processes, and data models for a global trading platform using Python, PostgreSQL, Airflow, and AWS.
Build and maintain GCP-based data pipelines and cloud services for enterprise clients, using Python, Java, SQL, and Looker.
Build and maintain full-stack financial systems for parking operators, using Java/Kotlin (Spring), React, PostgreSQL, and Kubernetes in a DevOps-driven environment.
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