11 of 11 Permanent Apache Spark Jobs in Central London

Strong full-stack experience with Python , Java (Spring Boot) , React , SQL, and relational databases. Hands-on experience with modern data engineering tools (e.g. Airflow, Spark, Kafka, dbt, Snowflake or similar). Experience with cloud platforms , containerisation (Docker/Kubernetes) , and CI/CD pipelines . Solid understanding of data ...

commodities markets or broader financial markets. Knowledge of quantitative modeling, risk management, or algorithmic trading. Familiarity with big data technologies like Kafka, Hadoop, Spark, or similar. Why Work With Us? Impactful Work: Directly influence the profitability of the business by building technology that drives trading decisions. Innovative Culture ...

DevOps and broader software engineering standards. Cloud experience (any platform). Previous mentoring experience. Nice to have: Snowflake or Databricks Spark, PySpark, Hadoop or similar big data tooling BI exposure (PowerBI, Tableau, etc.) Interview Process The process is fully structured, transparent, and efficient: Video call - high-level overview ...

security controls. Monitor, maintain and optimise data platforms to ensure performance and reliability. Skills and Experience Required: ETL development using Python or similar languages Apache Spark, NiFi, or Kafka Relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra) databases AWS and cloud-based data services Palantir Foundry Stakeholder Engagement ...

integration and API development (REST, SOAP) Informatica or Oracle Data Integrator SQL Server Integration Services (SSIS) Azure Data Factory or Azure Synapse Databricks or Apache Spark Amazon Redshift SQL Server or Oracle Database Oracle Integration Cloud or Business Objects Data Services Desirable Skills: Business intelligence tools such ...

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. ...

models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A/B testing methodologies, and experiment design. Solid background in ranking, recommendation ...

RNNs, Transformers) and when to apply them Strong SQL and data manipulation capabilities Experience working with large-scale datasets and distributed compute frameworks (e.g., Spark) Demonstrated ability to independently lead technical ML solution design Experience working in client-facing delivery environments Exposure to cloud-based ML platforms (AWS, Azure ...

engineering practices (clean code, testing, version control, code review) Proficient with large-scale data : strong SQL skills and familiarity with distributed data processing (e.g., Spark, Hive) for building training datasets, features, and analytical views Leadership & Collaboration Proven ability to lead through influence : aligning cross-functional stakeholders on problem definitions ...

ensure A-Level grades are included on your CV) Basic scripting knowledge in Python or Bash Excellent customer-facing skills You have a sales spark - while this role isn't a focused sales role, this is required due to the nature of the role A motivated self-starter with ...

scalable, resilient data platforms supporting Counterparty Credit Risk (CCR), trade processing, analytics, and regulatory reporting. The ideal candidate has deep hands‐on expertise in Spark, Scala, Python, and distributed data systems, with strong domain knowledge of financial and risk data. Hybrid working: The places that you work from … will be unable to work at home 100% of the time. Your Role: Design and build distributed batch and real‐time data pipelines using Spark (Core/SQL/Streaming) in Scala and Python. Architect scalable ingestion, transformation, and enrichment frameworks for trade, risk, and regulatory datasets. Lead solution ...