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Design and build scalable cloud-native AI data platforms and pipelines using Python, Spark, and Kafka to power machine learning and GenAI initiatives for enterprise clients.
Build and maintain AWS-based data pipelines and ML workflows, turning datasets into insights and scalable analytics for clients across industries.
Senior Data Engineer builds scalable Lakehouse architectures and ETL/ELT pipelines using Databricks, Spark, and cloud services to turn logistics data into BI insights and support analytics across Azure, AWS, or GCP.
Design and automate AWS-based data infrastructure using Terraform and Python, building scalable pipelines for ingestion, transformation, and validation.
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 cloud-based data pipelines and Lakehouse architectures using Azure, AWS, Databricks, and PySpark to deliver clean, scalable data for analytics and AI teams.
Designs and maintains scalable AWS data pipelines using S3, Glue, Lambda, Redshift, and EMR to integrate and deliver data for analytics and reporting.
Build and own scalable AI/ML data pipelines and real-time streaming systems using Python, Spark, Airflow, Kafka, and cloud services like SageMaker and Snowflake.
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 cloud-based data platforms using Databricks, SQL, Python, and cloud data warehouses to enable data-driven decisions for global clients.
Build and optimize AWS-based data pipelines and Redshift models to power BI and analytics for a large European telecom client.
Netguru is a trusted partner in digital commerce. The company helps leading brands modernize B2B solutions, marketplaces, and retail ecosystems. Since 2008, it has empowered businesses with cutting-edge technology,…
Senior Data Engineer designs and builds scalable data pipelines and warehouses, mentors junior engineers, and ensures reliable data delivery for analytics and business insights.
Senior Data Engineer builds and maintains ETL/ELT pipelines, data models, and quality checks using AWS, Spark, Python, and Databricks to deliver clean data for analytics and ML teams.
Senior Data Engineer builds scalable data platforms using cloud tools (Azure, GCP, AWS), Databricks, and modern warehouses (Synapse, BigQuery, Redshift, Snowflake) to enable data-driven decisions.
Design, build, and optimize large-scale data pipelines and warehouses for a finance-automation SaaS, ensuring data quality and accessibility for analytics and product teams.
Design and build scalable AWS-based data pipelines and cloud-native architectures to process large datasets, using services like Glue, Redshift, Lambda, and Spark.
Senior Data Engineer designs and builds scalable data platforms using cloud tools (Azure/GCP/AWS), Databricks, and modern warehouses (Synapse/BigQuery/Redshift/Snowflake) to enable data-driven decisions.
Build and maintain scalable data pipelines and AI-ready cloud infrastructure using Python, PySpark, and cloud platforms to support analytics and machine learning workflows.
Senior Data Engineer builds and optimizes large-scale ETL/ELT pipelines using Python, PySpark, SQL, and AWS services to deliver reliable, high-performance data solutions for global clients.
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