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The Snowflake Architect will design and implement scalable cloud data solutions while providing consulting services to clients. The role requires expertise in the Snowflake ecosystem, including AI/ML capabilities like Cortex, alongside data engineering tools such as dbt, Azure, and Python.
As the first dedicated data engineer, you will architect and own the full data stack, including ingestion, transformation, and warehouse infrastructure for a real-money gaming platform. You will work with Python, SQL, dbt, and orchestration tools to build reliable pipelines that support quantitative strategy and production systems.
Senior Data Engineer building and optimizing large-scale Spark/PySpark data processing engines, refactoring legacy SQL ETL into Python, and implementing medallion architecture with Delta Lake on Azure cloud platforms.
The Data Engineering Tools Developer builds internal Python-based frameworks, Streamlit applications, and reusable tools to improve the productivity and reliability of data pipelines. The role involves collaborating with data engineers and architects to standardize development, monitoring, and governance practices within a financial services environment.
Senior Data Engineer designing and building scalable data pipelines, driving cloud migration to Azure, and transforming large-scale datasets. Core tech: Azure Fabric, Azure Databricks, PySpark, Python, SQL, DBT, Snowflake, Docker, Kubernetes.
Build and maintain trusted, well-modeled datasets in BigQuery using dbt to power analytics and ML across a fintech platform, ensuring data correctness and collaborating with engineers and stakeholders.
The Data Platform Engineer will design, build, and maintain a declarative data platform to support ingestion, transformation, and consumption across the company. The role involves working with cloud data warehouses, orchestration tools, and infrastructure-as-code to ensure scalable and reliable data systems.
Data Engineer building scalable batch and streaming pipelines, data products, and AI-facing integration layers (e.g., MCP servers) for an internal Agentic AI ecosystem using Python, SQL, dbt, orchestration tools, and cloud data platforms.
Bachelor s or master s degree in computer science, Information Systems, or a related field. 8 years of data engineering experience (at least 2 years in financial services or regulated environments). Expert knowledge of…
In a few words Se anima a todos los posibles solicitantes a que se desplacen y lean la descripción completa del puesto antes de presentar su candidatura. Position: Data Engineer MLE Location: Madrid (Chamberí area).…
Location: Ghent, Belgium. ONTOFORCE helps life sciences organizations accelerate research and drug development by unlocking hidden insights from complex data. Our flagship platform, DISQOVER, is a life sciences data…
Machine Learning Reply is seeking a DevOps/ML Engineer to design and implement data-intensive AI solutions for clients using cloud infrastructure and MLOps practices. The role involves automating workflows, managing infrastructure, and collaborating with cross-functional teams to deliver production-ready machine learning applications.
Develops and scales quantitative data products for investment teams, bridging financial domain expertise with cloud-native data engineering (BigQuery, dbt) and analytics engineering to modernize reporting, AI-ready datasets, and visualization tools like Power BI and Streamlit.
The Senior Data Platform Analyst will oversee, optimize, and govern WestJet's enterprise data platforms, including Power BI, Microsoft Fabric, and Snowflake. The role focuses on capacity management, platform performance, and mentoring teams to ensure scalable and cost-effective data solutions.
As a Senior Data Engineer, you will design and build modern Snowflake data platforms and pipelines for clients while providing expert consulting on cloud architectures. You will work with technologies like Python, SQL, Airflow, and dbt to deliver scalable, secure, and efficient data solutions.
Build and maintain scalable data pipelines and ML systems for clinical trials, R&D, and drug manufacturing at a global pharma company’s applied AI team.
Senior Data Engineer building and maintaining a data platform (Dagster, dbt, AWS ECS, GCP BigQuery) and optimizing core ELT pipelines moving terabytes nightly from MySQL to BigQuery for a fashion e-commerce company.
Build and maintain a new Data Platform (Dagster, dbt, AWS ECS, GCP GBQ) serving as the foundation for other data teams, and own core ELT pipelines.
Builds and maintains data pipelines for ingesting, parsing, and structuring unstructured financial data (PDFs, HTML, XBRL) while integrating LLM-powered AI systems for retrieval and analytics in a FinTech context.
Builds and maintains the AI-driven infrastructure for Owner’s unified platform, integrating tools like websites, online ordering, CRM, and POS systems for local businesses, primarily restaurants.
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