6 of 6 Remote/Hybrid Parquet Jobs in the UK

standards such as metrics and use of test tools Here's a snapshot of the technologies that we use: Scala Apache Spark Databricks Apache Parquet Azure Cloud Platform Azure DevOps (Test plans, Backlogs, Pipelines) GIT We'd love to hear from you if you have: Good experience in creating ...

technology stack through reusable libraries, APIs, and robust engineering practices.Optimise performance, scalability, and reliability of quantitative applications.Skills required:Python data engineering stack: Pandas/Parquet/FastAPI/Jupyter/Airflow/Streamlit/RayExperience with high-performance data stores and query engines like Trino/SnowflakeExperience with financial ...

Storage, and SQL/NoSQL technologies. Experience monitoring and supporting production ML environments. Knowledge of data engineering practices and tools. Familiarity with GRIB, NetCDF, Parquet, and JSON is advantageous. Azure Data Scientist Associate certification is desirable. If you have the relevant skills and experience, please do apply promptly ...

desks and ability to analyse and address issues and queries quickly and effectively.Recent hands-on experience with Python plus SQL Server and ideally some Parquet exposure.Evidence of strong delivery throughout the entire lifecycle.Strong problem-solving skills and capability to write code quickly and accurately, plus experience of troubleshooting production ...

finance, high-yield, private credit, distressed, and the data pain points those teams have.Fluent in how data and quant teams actually consume APIs today. Parquet, DuckDB, Polars, Snowflake shares, not just pandas in a Jupyter notebook. You can rip through a notebook live on a call.Exposure to MEDDPICC/ ...

Flink), batch, and file-based vendor feeds (SFTP/managed file transfer), landing data from Product Engineering services into the lakeThe lake/lakehouse — Parquet, Trino, table formats, partitioning, and the physical and analytical modelling underneathThe serving/cache tier — powering customer-facing screeners and analytics at production latency … schema evolution, backfillsStrong on schema registries and contracts (Avro/Protobuf, evolution, breaking-change handling across producers and consumers) — not just dimensional modellingFluent in Parquet, Trino, streaming (Kafka/Flink), and lakehouse platforms (Snowflake/Databricks), and the throughput and cost engineering that comes with scaleProduct and governance instincts ...