7 of 7 Apache Spark Jobs in the City of London

you. You'll be joining a large-scale cloud data transformation programme, helping design, build and optimise enterprise data platforms using Python, Databricks and Spark within a modern Lakehouse environment. Key Responsibilities Design, develop and maintain scalable data pipelines using Python and Databricks. Build, optimise and support enterprise …/ELT workflows using Apache Spark and Delta Lake. Design and develop robust data models and Lakehouse architectures. Implement and manage data workflows within the Databricks ecosystem. Ensure high levels of data quality, governance and pipeline reliability. Optimise performance across large-scale distributed data processing platforms. Collaborate with ...

systems Comfortable building from scratch in a fast-moving, product-led environment Experience with vector databases and vector search in modern AI systems Desirable: Spark, Airflow, Kafka, Elasticsearch/OpenSearch, event-driven architectures Cloud experience (AWS, GCP or Azure) is a plus Why join High impact and ownership ...

datasets Preferred Qualifications Knowledge or interest in investment banking or financial instruments Experience with big data concepts, such as Lakehouse, ETL data pipelines (e.g. Spark, AWS Glue) Experience with near real time and event-based systems like Kafka ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital ...

compute cluster capabilities Advanced proficiency in Python, with extensive professional experience in building production applications and services Experience of modern cluster compute - Kubernetes, Spark, Hadoop Yarn, Ray, Airflow are some of the technologies we use Experience leading work in a formal software development environment alongside other engineers ...

market data normalisation. Experience handling time-series challenges such as timestamp precision, sequence gaps, duplicate and out-of-order events. Experience with distributed processing (Spark, Polars, Dask, Ray or similar). Experience with Kafka or similar streaming technologies. Familiarity with PostgreSQL, ClickHouse, Snowflake, Databricks, kdb+ or similar. Docker, Linux … market data engineering with proven experience building reliable, scalable data platforms. Our non-negotiable requirements are: Expert Python Strong SQL Scalable data pipeline development Apache Parquet Market data normalisation Automated data quality controls Deep tick and market data expertise Experience in MLOps is advantageous but not essential. We welcome ...

appropriate technologies for scalable analytics, trading strategy development, tick or time-series data, workflow automation and AI/ML-enabled use cases. Prefer Databricks, Spark and modern lakehouse patterns for scalable analytics where suitable, while recognising transferable experience with Snowflake and other enterprise data platforms. Ensure delivery choices balance … define OKRs, shape roadmaps and deliver enterprise data or analytics products. Hands‐on understanding of data technologies and modern analytics platforms, preferably Databricks/Spark and lakehouse patterns; Snowflake experience is relevant and transferable but Databricks experience is preferred. Experience with Python, SQL and production analytics workflows; familiarity with ...

APIs used by researchers and engineers across the firm. Ideal candidates have deep Python expertise, hands-on experience with modern cluster compute technologies (Kubernetes, Spark, Hadoop/Yarn, Ray, Airflow) and a track record of delivering scalable infrastructure in a multi-user #J-18808-Ljbffr ...