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Build and maintain scalable data pipelines and platforms using Spark, Scala, Kafka, and cloud tech to enable analytics and decision-making across BNP Paribas.
Senior Data Engineer builds scalable data pipelines, ETL/ELT processes, and cloud-based analytics platforms using Python, Spark, AWS, and modern data stacks to power AI-driven solutions.
Senior Data Engineer builds and scales reliable, high-quality data pipelines and governance at a global market-research analytics firm using Python, SQL, Airflow, Spark, and AWS.
Design and maintain scalable data pipelines and infrastructure for a European payment provider, ensuring clean, accessible data for analytics and reporting using PostgreSQL, ElasticSearch, and ETL processes.
Build and maintain scalable Azure data pipelines and architectures using Data Factory, Databricks, and Synapse to ingest, transform, and integrate data for analytics and reporting.
Senior Data Engineer builds and maintains scalable data pipelines and models for a leading aeronautics client, ensuring data quality and security while collaborating with analytics and AI teams using Python, SQL, Snowflake, and Airflow/DBT.
Senior Data Engineer to own and scale a GCP-based data warehouse, build robust pipelines, and unify diverse data sources for a leading online education group.
Build and maintain AWS-based data pipelines and ETL workflows using Python, Spark, and Glue to feed analytics and reporting systems.
SAS Data Engineer supporting users during DWH migration, refactoring SAS code, and optimizing data access for BI/analytics in an international team.
Build and maintain end-to-end data pipelines and warehouses in Snowflake, using Matillion, dbt, Azure Data Factory, and Power BI to deliver scalable, high-performance analytics solutions.
Build and optimize Azure-based data pipelines using SQL, T-SQL, and Databricks to support scalable cloud data solutions.
Build and maintain data pipelines and cleaning processes for a leading insurance company, ensuring reliable analytics and compliance.
Build and maintain reliable data pipelines and models for analytics, using SQL, PL/SQL, T-SQL, and cloud data warehouses to transform raw data into trusted business insights.
Build and maintain automated data pipelines in Python and GCP, cleaning and validating large datasets while integrating Google Sheets, BigQuery, and APIs.
Build and maintain scalable data pipelines and cloud architectures to ingest, transform, and serve reliable data for analytics and reporting across hybrid environments.
Build and maintain data pipelines and microservices on OpenShift, using SQL and Oracle/PostgreSQL to support banking-sector clients.
Build and own the data foundation: reliably land source data into Snowflake, process it on Databricks, and instrument clean product telemetry so data scientists can trust and use it.
Designs and maintains data pipelines using Microsoft Fabric and Azure tools to build scalable analytics platforms for enterprise clients.
Build and maintain scalable data pipelines and cloud infrastructure to move raw client data into clean, secure warehouses for BI and future AI/ML use.
Design and build data pipelines and backend services for AI-driven energy asset operations, integrating SCADA and corporate data in Microsoft Fabric and Power BI.
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