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Builds and maintains Ondo Finance’s foundational data platform in BigQuery, consolidating on-chain/off-chain data sources for analytics, risk, and decision-making in tokenized financial products. Owns ETL pipelines, Go-based data ingestion, and data infrastructure standards for a fully remote fintech startup.
Builds and maintains SAP BW/4HANA data pipelines, models, and BI solutions to integrate and transform data for reporting and analytics.
The Data Engineer designs and maintains scalable data pipelines and marts within a Databricks Lakehouse on Azure. The role focuses on data quality, governance, and collaboration with analytics teams to deliver reliable data products.
Builds and maintains backend services in Go and Python to collect, process, and serve fusion-energy experiment data for physicists and engineers.
The Data Engineer will lead the onboarding and integration of new data sources into the enterprise data platform using Snowflake. They will collaborate with stakeholders to build scalable data pipelines and contribute to data transformation and modelling efforts.
Designs and deploys large-scale experiments for retail clients, develops measurement methodologies, and conducts deep-dive analyses to guide business decisions using statistical modeling, Python/R, and SQL.
Builds a new data platform in Canada, designing Snowflake-based ELT pipelines, data models, and AI/ML-ready infrastructure while enabling BI tools like Metabase for data storytelling.
Build and maintain dbt-powered data models in Snowflake to support financial close and POS/payment reporting for a large Canadian enterprise.
Build and optimize scalable data pipelines and warehouses in Snowflake, using dbt and CI/CD to deliver clean, reliable financial data for analytics and reporting.
Builds a new portfolio management system’s Python backend and integrates Bloomberg for market data, using PostgreSQL/Snowflake/Azure to design scalable APIs and cloud infrastructure from scratch.
Build and maintain dbt models and SQL transformations in BigQuery/ClickHouse to power reliable analytics and reporting across health, education, and media products.
An internship automating data pipelines and building scalable backend systems for ING’s data management team, using Python and cloud tools to improve data workflows and collaboration with engineers/scientists.
Build and operate scalable, secure backend services in Go and TypeScript for a multi-tenant, event-driven cloud platform, using AWS services and infrastructure-as-code.
Lead a small team to build and maintain Numan’s data infrastructure, from ingestion to reporting, ensuring reliable insights for commercial decisions.
Designs and builds scalable data pipelines and infrastructure in Microsoft Fabric, focusing on ingestion, transformation, and CI/CD automation for a global media/agency network.
Designs, develops, and maintains data architecture and pipelines to transform raw data into processed data, ensuring scalability and reliability for business needs. Core technologies include Big Data tools (Spark, Airflow), SQL/NoSQL databases, and programming languages like Java/Python.
Designs, develops, and maintains data architecture and pipelines to transform raw data into processed formats, ensuring scalability, reliability, and performance for business operations. Core technologies include ETL/ELT, Big Data tools (Spark, Airflow), SQL/NoSQL databases, and programming languages like Java/Python.
Leads data engineering for a UK health-tech company, designing pipelines, managing a team of 2 engineers, and ensuring scalable, compliant data infrastructure to power analytics and business decisions across diagnostics, medication, and wellness platforms.
Leads and mentors data engineers to design, optimize, and govern cloud-based data pipelines, ensuring scalability, security, and compliance in a fully cloud-native environment.
Senior Data Engineer builds and maintains scalable data pipelines and platform components in Azure using Python/Scala, Spark, and Databricks to power ASOS’s ecommerce analytics and machine learning.
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