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Design and maintain data pipelines for security systems, optimizing Oracle databases with PL/SQL and ETL workflows to support Identity Governance and Zero Trust compliance.
Designs and maintains scalable cloud data pipelines using Databricks and Snowflake to turn raw data into actionable insights for clients.
Designs and builds scalable data pipelines and curated data products on Databricks using SQL, Python, and PySpark with a focus on governance and quality.
Senior Data Engineer builds cloud pipelines to move energy data from on-site systems to the cloud and helps integrate ML models for Ampowr’s Energy Management System.
Builds scalable data pipelines and AI-ready infrastructure for logistics and energy clients using Spark, Fabric, and cloud platforms like AWS/Azure/GCP.
Build and maintain RAG pipelines: clean and transform unstructured data, generate embeddings, and optimize vector indexes for retrieval quality.
Builds scalable data pipelines and cloud integrations using Databricks, Snowflake, and Microsoft Fabric to deliver data solutions for diverse clients.
Traineeship in data engineering and analytics, learning Python/R/Java to build pipelines and models that drive business decisions.
Build and optimize data pipelines and architectures for clients, using Python, SQL, and cloud platforms like AWS/Azure to process and integrate data at scale.
Build and optimize cloud-based data pipelines and ML infrastructure for client projects and internal AI tools using Python, Docker, Kubernetes, and GCP/AWS/Azure.
Principal Data Engineer designs and builds scalable Databricks-based data platforms, owning architecture from ingestion to consumption while guiding teams on Delta Lake, Unity Catalog, and governance.
Principal Data Engineer designs and builds scalable, sovereign data platforms for government and enterprise clients, integrating cloud-native pipelines, AI, and open-source tech like Kafka, Spark, and Kubernetes.
Lead a team to design, build, and maintain scalable data pipelines and architectures, ensuring high-quality data flows and governance for analytics and operations.
Leads end-to-end data engineering projects, designing scalable ETL/ELT pipelines and cloud-based data architectures while coaching a team of engineers to deliver reliable, high-impact data solutions for enterprise clients.
Build and maintain a self-serve data platform for a large classifieds marketplace, owning batch and streaming pipelines, lake management, and APIs that power analytics and ML workloads using Databricks, AWS, Spark, Python, Kafka, and Airflow.
Design and maintain scalable data pipelines and storage systems to power fraud detection, analytics, and reporting using Python, SQL, and tools like Airflow and ClickHouse.
Build and maintain scalable data pipelines and warehouses for a logistics platform, ensuring reliable data flows for shipping, customer insights, and financial reporting.
Build and maintain the marketing measurement stack—tracking, attribution, and privacy-safe data flows—to power paid campaigns and experiments across web, app, and server environments.
Build and deploy cloud-native data platforms on Kubernetes, containerizing workloads and integrating tools like Airflow and Spark while collaborating with data scientists to productionize models.
Build and optimize SAP BI dashboards and data models using SAC, Datasphere, and BW/4HANA for retailers, utilities, and public-sector clients.
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