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Owns backend systems for ingesting, transforming, and distributing real-time sports data to power Fliff’s gaming platforms with correctness and resilience.
Builds and scales a high-performance data platform using Java or Python and Kafka to support AI-driven services and high-volume data ingestion.
Build and scale high-volume audio data ingestion pipelines on GCP using Terraform and Docker, collaborating with AI researchers to improve Speechify’s models.
Designs and optimizes cloud-based ETL/ELT pipelines and data lakes using AWS, dbt, Airflow, and Terraform to deliver data products for analytics teams.
Senior Data Engineer builds and maintains scalable data ingestion pipelines and lakehouse infrastructure to power analytics, ML, and product features at an edtech platform.
Build AI-ready data pipelines and domain products in Microsoft Fabric and Snowflake, focusing on semantic annotation, vector stores, and RAG foundations for enterprise reuse.
Develop and maintain data ingestion and processing pipelines for satellite and Earth Observation data using Python in Linux environments.
Build and optimize data pipelines with dbt, SQL, and Python to deliver AI-driven insights for an orthodontic clinic network.
Builds and maintains data pipelines and SQL queries to track supply-chain defects and delivery performance, enabling real-time analytics and process improvements for Amazon’s EU inbound logistics.
Build and maintain data lake components and production-grade ingestion pipelines for analytics, ML, and product features at an online education platform.
Build and maintain data pipelines and ETL workflows in Python, orchestrating data ingestion from multiple sources for an AI-powered fintech using Kubernetes, Airflow, and cloud platforms.
Build and maintain a scalable data lakehouse and pipelines to feed BI, analytics, and AI workloads for a product company.
Lead a team to build and maintain Azure-based data pipelines and storage, using Databricks, Synapse/Fabric, and CI/CD to ensure high-quality, performant data flows.
Build and maintain core reference-data pipelines in Snowflake and AWS for a global investment bank, using Python, Airflow, and modern cloud-native tooling.
Build the core AI-powered backend for an operating system serving parts and equipment industries, owning data pipelines, APIs, and legacy system integrations in a fast-growing startup.
Senior Data Engineer to build and maintain a real-time, scalable data platform handling streaming and batch processing for a multi-year funded programme.
Build and maintain scalable data pipelines using PySpark, Python, and Azure Data Factory to ingest and transform data for reliable analytics and reporting.
Design and maintain scalable ETL pipelines, data warehouses, and real-time streaming solutions using SQL, Python, and cloud platforms like AWS/Azure/GCP.
Designs and maintains AI-ready data pipelines, feature stores, and curated datasets to power machine learning models, generative AI, and real-time analytics using cloud-native tools.
Designs and builds secure, scalable APIs (REST/SOAP) for data exchange, integrates systems with third-party services, and ensures compliance and performance using Azure and Python.
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