16 of 16 Apache Spark Jobs in Central 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 ...

root‐cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark . Working knowledge of common data formats such as JSON , Avro and Parquet . Technology Environment The role will involve working with … should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised ...

production-grade solutions using BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer . Frameworks & Storage: Strong understanding of batch/streaming tools (e.g., Apache Spark, Apache Beam ) and when to apply different storage paradigms (relational, columnar, document, data lakes). Modern Best Practices: Active practice with ...

considering: We are looking for an experienced AWS Databricks Engineer with strong hands-on expertise in Databricks, AWS cloud services, PySpark, Spark SQL, Delta Lake, Python, SQL, and data engineering. The candidate will be responsible for designing, developing, optimizing, and supporting scalable data pipelines and lakehouse solutions … time. Your Role: Design, develop, and maintain scalable data pipelines using Databricks on AWS. Build and optimize data processing frameworks using PySpark, Spark SQL, Python, Delta Lake, and Databricks notebooks. Develop end-to-end ETL/ELT pipelines for ingestion, transformation, validation, and consumption. Work with AWS services such ...

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 ...

preparation. Machine learning and statistical methods, including model validation. Data analytics and visualisation techniques. Processing large datasets using batch or streaming tools such as Apache Spark. Data acquisition and fusion approaches. Cloud platforms (ideally AWS) and cloud-based data science solutions. DataOps principles and practices. Structured and unstructured databases. ...

ideal candidate will have a strong programming background in Python or Java, knowledge of SQL, and experience with data processing frameworks such as Apache Spark. Responsibilities include enhancing data pipelines, ensuring data quality, and collaborating with engineering teams. The position is located in London and offers significant growth opportunities ...

data models and outputs Set up monitoring and ensure data health for outputs What we are looking for Proficiency in Python, with experience in Apache Spark and PySpark Previous experience with data analytics softwares Ability to scope new integrations and translate user requirements into technical specifications What ...

Desirable SC clearance alongside NPPV3 Functional/typed Scala — Cats, Cats Effect, FS2, http4s, Circe — a strong plus Streaming/big-data frameworks (Kafka, Spark, Flink) for integrating with partner pipelines Government, policing or law-enforcement data experience Data lineage, provenance, audit or integrity/verification tooling Secure ...

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 ...

streamline operations. At Chainalysis, we are at the forefront of this development. Technologies in Use Technologies we use include: AWS serverless architectures Kubernetes PostgreSQL Spark Typescript Terraform Kafka Github (including Github Actions) Java Data Platform Development We are building the data platform for blockchain, cryptocurrency, and web3. The Protocol ...

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 ...

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 ...

software and site reliability engineering. Preferred: Experience with distributed ML frameworks such as Horovod or TensorFlow Distributed. Familiarity with data engineering pipelines such as Apache Airflow or Apache Spark. Knowledge of chaos engineering tools and compliance frameworks such as GDPR, SOC 2, or ISO 27001. Relocation benefits ...

replication tool, and Waggle Dance, a federation service that allows access to data lake tables across multiple catalogs. Recently, we added Hive support to Apache Iceberg, a high-performance open table format for large analytic datasets that underpins many modern Lakehouse architectures. We guarantee you’ll learn … scalability, reliability, and observability. Strong knowledge of the JVM and server-side Kotlin/Java programming. Solid understanding of the Hadoop ecosystem, including Spark, Hadoop, and Hive. Strong experience with cloud platforms and data infrastructure, especially AWS, including EMR, S3, and Glue. Experience working in Agile environments and contributing ...