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Build and optimize scalable data pipelines, ETL processes, and cloud-based data architectures using Python/Java/Scala, Spark, Kafka, and cloud platforms (AWS/Azure) to support large-scale analytics and client projects.
Maintains and scales Linux/Windows servers, databases (PostgreSQL, MSSQL, etc.), and real-time data pipelines (Kafka, Flink) while building data warehouses and IoT integrations.
Build and maintain scalable data pipelines and lakehouse platforms using Databricks, Spark, Delta Lake, and Python to support anti-financial-crime analytics and reporting for global PwC clients.
Builds and optimizes SQL Server-based data warehouses and ETL pipelines with SSIS, then models tabular datasets in Power BI/SSAS for business reporting.
Lead a team to build and optimize Databricks-based ETL/ELT pipelines using Python/SQL, Delta Lake, and cloud platforms (Azure/AWS/GCP) for large-scale data processing.
Lead a Databricks-based data engineering team to build and optimize ETL/ELT pipelines, Delta Lake tables, and cloud data warehouses using Python, SQL, and Azure/AWS/GCP.
Senior Data Engineer builds scalable Google Cloud data platforms (BigQuery, pipelines) to enable clients’ data-driven decisions, using SQL/Python and modern warehousing concepts.
Build and maintain Mettler Toledo’s data platform, creating scalable pipelines and ensuring high-quality data flows for analytics and AI/ML using Databricks, Snowflake, and Python.
Build and maintain data pipelines and warehouses using Oracle, PostgreSQL, BigQuery, Informatica PowerCenter, Kafka, and Python to feed analytics and ML workloads.
Own and evolve Vatix’s AWS-based data warehouse (Redshift, Postgres RDS) and pipelines that power real-time customer dashboards, while setting the technical direction for data engineering and integrating third-party systems.
Build and optimize scalable data pipelines using Databricks, Spark, and Azure to power AI/ML solutions for global enterprises across aerospace, energy, and automotive sectors.
Lead the design and development of data architectures and pipelines for a leading spirits company, ensuring data quality and mentoring junior engineers.
Design and build scalable AWS-based data pipelines using PySpark and AWS Glue, then monitor and optimize them for performance and reliability.
Build and optimize cloud-based data platforms using Databricks, SQL, Python, and cloud data warehouses to enable data-driven decisions for global clients.
Senior Python Data Engineer builds and maintains scalable data pipelines and models for regulatory reporting in finance, using Python, Spark, and Databricks to process high-volume batch and streaming data.
Senior data engineer builds and optimizes ETL pipelines and data warehousing solutions for Credit and ESG systems using SQL, Informatica PowerCenter, and Oracle.
Design and maintain Azure-based security data pipelines, ETL processes, and analytics platforms to centralize and secure enterprise data across multi-cloud environments.
Build and optimize ETL/ELT pipelines in Google Cloud, transforming raw data into reliable datasets for analytics and reporting using BigQuery, Data Vault, and Airflow.
Designs and builds scalable data lake and warehouse solutions using SQL, Python, and cloud tools like Google Cloud Platform and Informatica Power Center.
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