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Streaming Data Engineer: Build Scalable Pipelines & ML Data
Design and build scalable data pipelines and platforms using Python/Java and Spark to ensure high-quality, performant data flows for analytics and ML.
Data Engineer
Build and optimize data pipelines and search systems using Python, Spark, and Azure/Databricks to power AI-driven discovery workflows for a global team.
Data Engineer
Designs and builds scalable data pipelines and warehouses using cloud tools (AWS/Azure), SQL/NoSQL, and big-data frameworks (Spark, Kafka) to enable analytics and ML for clients.
Remote Senior Big Data Engineer (Lakehouse & Pipelines)
Build and optimize data pipelines and lakehouse models using Spark/PySpark and SQL, integrating diverse data sources with quality controls.
Data Engineer
Build and maintain data pipelines, warehouses, and lakes using SQL, Python, Spark, and cloud platforms to power analytics and AI products.
Big Data Engineer — Spark Pipelines (Python/Scala)
Build and enhance Big Data pipelines for a banking client using Python/Scala and Spark, applying data warehouse principles and engineering best practices.
Senior Data Engineer
Design and build scalable data pipelines and warehouses using Python, SQL, and Spark to feed analytics and ML systems for clients.
Data Engineer (Databricks)
Build and maintain scalable data pipelines on Databricks, using Python and cloud platforms (AWS/Azure/GCP) to ingest, transform, and secure large datasets for analytics.
Senior Data Engineer
Senior Data Engineer builds high-performance data pipelines and lakehouse architecture using ClickHouse, Postgres, and open-source tools to power real-estate analytics and products.
Data Engineer: Spark, Airflow & Cloud Pipelines
Builds and maintains scalable data pipelines using Spark, Databricks, Python and SQL to process large media datasets and ensure data quality.
Middle Data Engineer
Designs and maintains scalable data pipelines and warehouses for analytics and ML using Snowflake, dbt, ADF, and Azure; writes efficient SQL and Python to process large datasets.
Senior Data Engineer
Build and maintain GCP-based data pipelines (batch/streaming) for analytics and ML, using BigQuery, Dataflow, Pub/Sub, Kafka, and ClickHouse.
Data Engineer (Contractor)
Build and maintain scalable data pipelines and infrastructure to ensure high-quality, trusted data for analytics and decision-making at a fintech payments company.
Staff Data Engineer
Build and maintain a globally distributed data platform using AWS, Snowflake, and Spark to power analytics and ML for Zendesk’s customers.
GCP Data Engineer
Designs and builds GCP-based data pipelines, warehouses, and storage systems using BigQuery, Airflow, and Python; troubleshoots performance issues and mentors junior engineers.
Software Architect
Designs and leads Paymentus’s enterprise payments platform, defining scalable microservices, APIs, and data flows while mentoring engineers and translating business needs into technical solutions.
Mid-Level Data Engineer: Cloud Pipelines & Analytics
Builds and maintains cloud-based ETL pipelines and data architectures using Python, SQL, and Spark to enable analytics and reporting.
Remote Azure Databricks Data Engineer — Lakehouse & Pipelines
Designs and builds scalable Azure Databricks Lakehouse pipelines using Spark and Azure Data Factory to power analytics and ensure data quality.
Data Engineer – Data Platform
Builds and maintains scalable data pipelines for Allegro’s clickstream, ensuring high-quality data for AI agents and business dashboards using Python, Spark, and streaming validation.
Data Engineer
Designs and builds cloud-based data pipelines and ETL workflows on Azure or GCP, using Python/Java/Scala, Spark, Kafka, and Airflow to modernize and migrate enterprise data systems.