12 of 12 Remote Parquet Jobs

for modern data and platform technologies. Nice to Have: Experience implementing data governance and observability stacks (lineage, data contracts, quality monitoring). Knowledge of data lake formats (Delta Lake, Parquet, Iceberg, Hudi). Familiarity with containerisation and streaming technologies (Docker, Kubernetes, Kafka, Flink). Exposure to lakehouse or medallion architectures within Databricks. More ❯

for modern data and platform technologies. Nice to Have: Experience implementing data governance and observability stacks (lineage, data contracts, quality monitoring). Knowledge of data lake formats (Delta Lake, Parquet, Iceberg, Hudi). Familiarity with containerisation and streaming technologies (Docker, Kubernetes, Kafka, Flink). Exposure to lakehouse or medallion architectures within Databricks. More ❯

for modern data and platform technologies. Nice to Have: Experience implementing data governance and observability stacks (lineage, data contracts, quality monitoring). Knowledge of data lake formats (Delta Lake, Parquet, Iceberg, Hudi). Familiarity with containerisation and streaming technologies (Docker, Kubernetes, Kafka, Flink). Exposure to lakehouse or medallion architectures within Databricks. More ❯

Kubernetes, Docker, and cloud-native data ecosystems. Demonstrable experience with Infrastructure as Code tools (Terraform, Ansible). Hands-on experience with PostgreSQL and familiarity with lakehouse technologies (e.g. Apache Parquet, Delta Tables). Exposure to Spark, Databricks, and data lake/lakehouse environments. Understanding of Agile development methods, CI/CD pipelines, GitHub, and automated testing. Practical experience monitoring More ❯

Kubernetes, Docker, and cloud-native data ecosystems. Demonstrable experience with Infrastructure as Code tools (Terraform, Ansible). Hands-on experience with PostgreSQL and familiarity with lakehouse technologies (e.g. Apache Parquet, Delta Tables). Exposure to Spark, Databricks, and data lake/lakehouse environments. Understanding of Agile development methods, CI/CD pipelines, GitHub, and automated testing. Practical experience monitoring More ❯

/Sub) * Observability stacks (OpenTelemetry, Prometheus, Grafana) * IaC (Terraform), security-by-design, OAuth/OIDC, secrets management * Batch & streaming data processing (Spark/Flink/Beam) or columnar analytics (Parquet/Arrow) Career Paths (we're hiring multiple profiles): * Go Backend (API-first): Own product APIs, performance, reliability. * Go Platform (ML-first): Focus on data lake, pipelines, model serving. More ❯

/Sub) * Observability stacks (OpenTelemetry, Prometheus, Grafana) * IaC (Terraform), security-by-design, OAuth/OIDC, secrets management * Batch & streaming data processing (Spark/Flink/Beam) or columnar analytics (Parquet/Arrow) Career Paths (we're hiring multiple profiles): * Go Backend (API-first): Own product APIs, performance, reliability. * Go Platform (ML-first): Focus on data lake, pipelines, model serving. More ❯

will create secure, efficient, and scalable environments for our data platforms. You will leverage cloud-native technologies and AWS tools such as AWS S3, EKS, Glue, Airflow, Trino, and Parquet, while preparing to adopt Apache Iceberg for even greater performance and flexibility. You'll tackle high-performance data workloads, ensuring seamless execution of massive queries, including 600+ billion-row More ❯

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 ❯

analytic datasets. Ideally you have experience of Python and associated common data processing packages. You will have used these to process data from databases or other sources, for example, parquet data stored in a data lake You're passionate about the tools you use to make development as efficient as possible - for example, you may have experience with git More ❯

Overview All our office locations considered: Newbury & Liverpool (UK); Šibenik, Croatia (considered) We're on the hunt for builders. Not in construction, but a designer and builder of systems for all things data related, helping us conquer the Data World. More ❯

on experience with Azure cloud technologies: Synapse, Fabric, AzureML, ADX, ADF, Azure Data Lake Storage, Event Hubs. Experience with visualisation tools such as Power BI and Streamlit. Familiarity with Parquet and Delta Parquet formats. Strong data modelling and architecture knowledge across SQL and NoSQL databases. Understanding of the software development lifecycle and ML-Ops. Knowledge of advanced statistical More ❯