1 to 25 of 90 Apache Spark Jobs in the UK

financial services organisation Your new role We are seeking a Data Engineer to support the replacement of a legacy ETL tool with a modern Apache Spark based data platform. This is a hands-on engineering role focused on building and supporting Spark jobs, with an emphasis … performance, reliability, and scalability.The role is focused on building nonperformance Apache Spark jobs, with a strong emphasis on performance optimisation. It is primarily Java-based, with Python strongly encouraged; experience across Java, Python, and Scala is ideal, with Java and Python being the preferred combination.The role sits within ...

financial services organisation Your new role We are seeking a Data Engineer to support the replacement of a legacy ETL tool with a modern Apache Spark based data platform. This is a hands-on engineering role focused on building and supporting Spark jobs, with an emphasis … Engineer. You will be responsible for development work, sprint delivery, demos, documentation, and stakeholder engagement. This position suits a mid-level engineer with strong Spark development experience rather than design, infrastructure, or management responsibilities. What you'll need to succeed Strong hands-on experience with Apache Spark ...

looking for: · 3+ years of professional Python development experience as a Data Platform Engineer, using AWS. · Experience developing and deploying Serverless technologies, provisioning Apache Airflow, and using infrastructure as code such as AWS CloudFormation or Terraform. · Takes a collaborative approach to problem solving and breaking down complex problems, whilst … with software engineering requirements and specifications. · Good interpersonal skills, positive can-do attitude and willing to help other members of the team. · Understanding of Apache Spark, Apache Trino or other big data and machine learning systems. · Exposure to using AI tools to enhance productivity and quality ...

with NoSQL databases. Experience with vector databases used in modern AI systems. Strong programming experience in Python Experience within the following technologies is desirable - Apache Spark, Apache Airflow, Kafka, Elasticsearch/Open Search, PostgreSQL, MongoDB, Pandas, Polars About the Package £100k - £110k on the base ...

NoSQL technologies Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP) Experience with big data technologies such as Spark, Hadoop, or Kafka Proficiency with ETL/ELT tools and frameworks (e.g. Airflow, dbt, Informatica) Strong programming skills in Python, Java, Scala, or similar Experience ...

with Red Hat OpenShift and Ceph storage platforms Programming experience (e.g. Python, JavaScript) Experience working with event streaming and data pipeline technologies (e.g. Kafka, Apache NiFi, Apache Spark) Experience delivering multi-system integration projects within defence, government, or highly regulated environments Experience implementing and configuring training simulation ...

with Red Hat OpenShift and Ceph storage platforms Programming experience (e.g. Python, JavaScript) Experience working with event streaming and data pipeline technologies (e.g. Kafka, Apache NiFi, Apache Spark) Experience delivering multi-system integration projects within defence, government, or highly regulated environments Experience implementing and configuring training simulation ...

with Red Hat OpenShift and Ceph storage platforms Programming experience (e.g. Python, JavaScript) Experience working with event streaming and data pipeline technologies (e.g. Kafka, Apache NiFi, Apache Spark) Experience delivering multi-system integration projects within defence, government, or highly regulated environments. Experience implementing and configuring training simulation ...

computer science, IT or a related field, or in bioinformatics with a demonstrated IT expertise Experience in big data technologies and frameworks, such as Apache Spark, Hadoop or similar platforms Hands-on experience with CI/CD (GitLab CI/GitHub Actions) Familiarity with Java Familiarity with Google ...

Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps & Deployment Model lifecycle management CI/CD pipelines Containerization (Docker, Kubernetes desirable) Model packaging and REST APIs Cloud & Tools (Any combination ...

Strong programming experience in Java (preferred) or Python Experience building ETL/ELT or streaming data pipelines Hands-on experience with Kafka, Flink, or Spark (streaming experience preferred) Good understanding of stream-processing concepts (event time, state, backpressure) Experience with cloud platforms (AWS preferred; Azure or GCP also considered ...

data estate. Deep expertise in Microsoft Azure cloud services - ADF, ADLS, Synapse, Purview. Databricks - Delta Lake architecture, optimisation and advanced data processing. Apache Spark for large-scale distributed computing and performance tuning. Microsoft Fabric - OneLake and DirectLake integration. Azure Synapse Analytics for enterprise-scale data warehousing. Infrastructure ...

experience in data engineering or large-scale data platforms Strong programming skills in Java (preferred) or Python Hands-on experience with Kafka, Flink, or Spark, with a preference for streaming technologies Solid understanding of real-time data processing concepts such as event time, state handling, and backpressure Experience building ...

schema). Version Control Practical experience with Git (branching, merging, pull requests). Preferred Qualifications (A Plus) Experience with a distributed computing framework like Apache Spark (using PySpark). Familiarity with cloud data services ( AWS S3/Redshift, Azure Data Lake/Synapse, or Google BigQuery/Cloud … Storage ). Exposure to workflow orchestration tools ( Apache Airflow, Prefect, or Dagster ). Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. ...

models are always running, always accurate, and always improving. Key Responsibilities ML Pipeline Orchestration & Automation Own and extend Circadia’s ML pipeline orchestration using Apache Airflow, including training, evaluation, and deployment workflows. Build and maintain automated pipelines for model retraining, validation, and promotion across development, staging, and production environments. … closely related infrastructure role. Strong proficiency in Python for ML pipeline development, tooling, and automation. Hands-on experience with ML pipeline orchestration tools, particularly Apache Airflow. Experience with model registries and experiment tracking platforms (MLflow preferred). Experience deploying and operating ML workloads on AWS (Batch ...

code for data workloads (Terraform or Bicep) * Databricks - Delta Lake, Unity Catalog, job cluster vs interactive cluster trade-offs, cost-aware compute management, Spark job optimisation * Relational databases: PostgreSQL at production scale - query optimisation, indexing strategies, table partitioning, replication, schema design for both OLTP and analytical workloads * MongoDB - document … documented data products * Nice to Have * Financial markets data - market data feeds (Bloomberg, Refinitiv), tick data, trade history, reference data, or instrument master management * Apache Spark or Flink for large-scale stream and batch processing beyond the Databricks ecosystem * dbt or equivalent SQL transformation layer; experience building ...

analytical data modeling in BigQuery using dbt . Build reliable data pipelines utilizing SQL, Python, and distributed processing frameworks (Apache Spark, Scio, Beam, or Flink). Develop clear, story-driven dashboards using tools like Looker or Tableau . Champion data quality , implement CI/CD for dbt models ...

experience working with data warehouses. Solid understanding of ETL/ELT design and data pipeline optimisation. Experience with big data frameworks such as Apache Spark, and exposure to streaming technologies like Kafka. Strong problem-solving skills and the ability to collaborate effectively across teams. What's on offer ...

with cross-functional teams to deliver data-driven solutions Support data modelling, governance, and quality initiatives What were looking for Experience with Python, SQL, Spark (and ideally Scala) Hands-on delivery of ML solutions in production Exposure to cloud platforms (AWS, Azure, or GCP) Understanding of DevOps, containers ...

focus on production-quality code • Solid understanding of ETL processes and best practices • Experience with SQL/NoSQL databases and big data tools (e.g. Spark, Pulsar) • Hands-on experience with cloud platforms (AWS, Azure, or GCP) • Experience developing and deploying data services end-to-end • Strong stakeholder communication ...

focus on production-quality code • Solid understanding of ETL processes and best practices • Experience with SQL/NoSQL databases and big data tools (e.g. Spark, Pulsar) • Hands-on experience with cloud platforms (AWS, Azure, or GCP) • Experience developing and deploying data services end-to-end • Strong stakeholder communication ...

focus on production-quality code • Solid understanding of ETL processes and best practices • Experience with SQL/NoSQL databases and big data tools (e.g. Spark, Pulsar) • Hands-on experience with cloud platforms (AWS, Azure, or GCP) • Experience developing and deploying data services end-to-end • Strong stakeholder communication ...

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 ...

What the role entails: Some of the main duties of the Data Engineer will include: Develop high-performance data pipelines using Python (Pandas) or Spark within Palantir Foundry, ensuring seamless data transformation and integration to support analytics, reporting, and machine learning use cases across the enterprise. Design and implement ...

auditable, lineage-aware, idempotent, and resilient in regulated environments. Implement robust data quality controls including testing, validation, monitoring, and alerting. Drive performance optimization across Spark and Snowflake workloads. Partner with Product, Engineering, DevOps, and Regulatory teams to translate requirements into scalable technical designs. Improve engineering standards, processes, and tooling ...