11 of 11 Polars Jobs in the UK

outcomes. Key Skills and Experience required Extensive background in delivering production-grade, data-centric applications for quantitative trading and analytics, with demonstrated expertise in: The python data engineering stack (Polars, Parquet, FastAPI, Jupyter, Airflow, Streamlit, Ray) High-performance data stores and query engines (Starburst, Snowflake) Real-time streaming analytics technologies (Kafka, Flink) Cloud container technologies (AWS, Azure, GCP, Docker, Kubernetes More ❯

in data-centric projects. Experience in developing and maintaining pipelines and infrastructure for products or applications, at scale. Strong knowledge of the Python Data Science stack (e.g., pandas/polars, scikit-learn). Ability to independently develop and maintain robust Python-based ETL/ELT data pipelines. Ability to independently develop LLM-based tools/products (e.g., RAG workflows). More ❯

data governance and quality standards across the platform. Collaborate with cross-functional teams to translate business challenges into technical solutions. Tech Stack Includes: Python, SQL, Azure, Postgres, Langchain, Ollama, Polars, GitLab CI/CD, Systemd, Ansible Ideal Candidate Profile: Significant experience as a Data Science or ML Engineer, with leadership responsibilities. Strong Python skills and experience with cloud-based data More ❯

data governance and quality standards across the platform. Collaborate with cross-functional teams to translate business challenges into technical solutions. Tech Stack Includes: Python, SQL, Azure, Postgres, Langchain, Ollama, Polars, GitLab CI/CD, Systemd, Ansible Ideal Candidate Profile: Significant experience as a Data Science or ML Engineer, with leadership responsibilities. Strong Python skills and experience with cloud-based data More ❯

and SQL for data mining; additional experience and knowledge of Big Data tools preferred. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow More ❯

and SQL for data mining; additional experience and knowledge of Big Data tools preferred. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow More ❯

interest in mentoring junior engineers. Familiarity with data-centric workflows and pipeline orchestration (e.g., Apache Airflow). Proficiency in data validation, anomaly detection, or debugging using tools like Pandas, Polars, or data.table/R. Experience working with AWS or other cloud platforms. Knowledge of building and monitoring high-performance, concurrent services. Additional Information We offer a Friends of Voleon Candidate More ❯

Proficiency in Git, including knowledge of branching strategies, merge mechanisms, and repository management Demonstrated ability to build and maintain test automation frameworks and CI/CD pipelines Experience with Polars Perks & Benefits Benefits package including Restricted Stock Units (RSUs), family health insurance, and contributions to private pension plans Fitness reimbursement Work anywhere Veeva's headquarters is located in the San More ❯

level experience Advanced skills in Python and strong fluency in SQL Experience working in cloud-based environments (preferably Azure) Hands-on experience with tools such as Postgres, Langchain, Ollama, Polars, GitLab CI/CD, and Unix-based systems Proven track record of deploying ML models into production and managing lifecycle Comfortable designing data services/APIs and supporting self-serve More ❯

and Python programming. Extensive experience working within a cloud environment. Experience with big data technologies (e.g. Spark, Databricks, Delta Lake, BigQuery). Experience with alternative data technologies (e.g. duckdb, polars, daft). Familiarity with eventing technologies (Event Hubs, Kafka etc ). Deep understanding of file formats and their behaviour such as parquet, delta and iceberg. What we offer We want More ❯

and spoken English) - experience leading meetings or sessions would be ideal. An understanding of appropriate communication styles for different client seniorities. Experience with Python (and pyspark/pandas/polars), or another programming language would be beneficial. Differentiators We would particularly like to see applicants who: Can demonstrate a strong proactive attitude towards learning, developing, and improving their skillsets. We More ❯