126 to 150 of 551 Apache Spark Jobs in the UK

years in a team leadership or mentorship role. Strong technical background in building and maintaining data pipelines and platforms using tools like Spark, dbt, Airflow, Kafka, or Databricks. Proficiency in one or more programming languages (e.g., Python, Scala, or Java) and SQL.Experience with cloud data platforms (e.g. ...

understanding of Terraform enterprise. Experience in delivering system design, application development, testing, and operational stability. Knowledge of Big Data distributed compute frameworks like Spark, Glue, MapReduce etc. Excellent troubleshooting, analytical, and communication skills. Preferred Qualifications, Capabilities, and Skills: Multi Region disaster recovery setup, monitoring and testing. Experience in Data ...

data pipeline orchestration tools* Containerisation (Docker, EKS, AKS, Kubernetes)* Proficiency in CI/CD principles and tools* Familiarity with open-source data tools (e.g., Spark, Kafka, PostgreSQL)* Infrastructure as Code (Terraform, Ansible)* Air-gapped development* Automation* Client/stakeholder management* Public sector domain understanding* Technical architecture**Experience:*** You will ...

background in software engineering, product management or data analytics. Strong proficiency in Python or Java, SQL, and data pipeline frameworks (e.g., Airflow, dbt, Spark), with solid experience with the AWS ecosystem. Excellent problem-solving skills and ability to work in a fast-paced environment. Bachelor’s degree in Computer ...

Risk, XVA, CCR, FRTB, portfolio risk, fixed income analytics, securitised products, liquidity risk, or managed risk-as-a-service solutions. Familiarity with Snowflake, Databricks, Spark, AWS, Azure, Confluence, Azure DevOps, Git, Tableau, Power BI, message queues, or comparable tools and platforms. Knowledge of market data vendors, data mastering, golden ...

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 EnvironmentThe role will involve working with a modern and evolving … 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, KafkaData formats: JSON, Avro, ParquetPlatforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQEngineering and deployment: CI/ ...

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. For More Experienced CandidatesStronger ownership of technical design across multiple datasets … 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, KafkaData formats: JSON, Avro, ParquetPlatforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQEngineering and deployment: CI/ ...

similar data-focused role Strong SQL and Python development skills Experience building and supporting scalable data pipelines and transformation processes Hands-on experience with Apache Spark, Databricks, dbt and cloud-based data platforms Good understanding of data modelling principles, data lakes and data warehouse architectures Experience working with … Essential: Degree in Computer Science, Software Engineering, Data Engineering, Information Systems, Mathematics or a related discipline; or equivalent practical experience Desirable: Relevant certifications in Spark, cloud technologies, data engineering or software engineering practices Why should you apply? We're not a perfect place - but we're a people place. ...

working with cloud‐native technologies, and applying robust software engineering practices. Key Responsibilities Design, develop, and optimise scalable, testable data pipelines using Python and Apache Spark. Implement batch workflows and ETL processes adhering to modern engineering standards. Develop Cloud-Based Workflows Orchestrate data workflows using AWS services such … Glue, EMR Serverless, Lambda, and S3. Contribute to the evolution of lakehouse architecture leveraging Apache Iceberg. Apply Software Engineering Best Practices Use version control, CI/CD pipelines, automated testing, and modular code principles. Participate in pair programming, code reviews, and architectural design sessions. Data Quality & Observability Build monitoring ...

decisions, documentation and continuous improvement initiatives. Key Skills & Experience Proven experience as a Data Engineer within production environments. Strong hands-on experience with Databricks, Apache Spark, Delta Lake, Python and SQL. Experience building and supporting scalable ETL/ELT pipelines. Strong understanding of distributed data processing and data ...

taking customers from EDW to the full capabilities of the Data Intelligence Platform. Demonstrated competence in the Lakehouse architecture including hands-on experience with Apache Spark, Python and SQL Excellent communication skills; both written and verbal Public Cloud Architecting: Hands-on experience designing and implementing big data architectures ...

comfort working through ambiguity. Desirable MLOps excellence: reproducible pipelines, model versioning, CI/CD, observability, and automated evaluation. Data engineering: proficiency with Databricks, Apache Spark, Delta Lake, MLflow, and SQL; experience integrating datasets and maintaining data quality. Model training and optimisation: experience with pre‐training, fine‐tuning, distributed ...

Risk, XVA, CCR, FRTB, portfolio risk, fixed income analytics, securitised products, liquidity risk, or managed risk-as-a-service solutions, familiarity with Snowflake, Databricks, Spark, AWS, Azure, Confluence, Azure DevOps, Git, Tableau, Power BI, message queues, or comparable tools and platforms, knowledge of market data vendors, data mastering, golden ...

/CloudFormation). Cloud experience with AWS, Azure or GCP (networking, IAM, storage, compute), including secure architecture principles. Experience with data platforms and pipelines (Spark, Airflow, Kafka, dbt or similar) and working with large-scale datasets. Knowledge of model serving patterns (REST/gRPC, batch scoring, streaming inference ...

grade code Distributed Data Processing Experience building and operating: batch processing systems distributed data systems near real-time streaming pipelines Familiarity with: Kafka Flink Spark Databricks experience is a strong plus Databases & Data Warehousing Comfortable working with: RDBMS data warehousing solutions Strong understanding of data modelling aligned with business ...

understanding of Terraform enterprise. Experience in delivering system design, application development, testing, and operational stability. Knowledge of Big Data distributed compute frameworks like Spark, Glue, MapReduce etc. Excellent troubleshooting, analytical, and communication skills. Preferred Qualifications, Capabilities, and Skills Multi Region disaster recovery setup, monitoring and testing. Experience in Data ...

Snowflake, Databricks). Experience with data integration (ETL/ELT, APIs). Familiarity with cloud data platforms (AWS, Azure, GCP) and big data (Hadoop, Spark, Kafka) is a plus. Domain Knowledge Exceptional understanding of the Funds business lifecycle, financial instruments, market data, and investment operations. In-depth knowledge ...

twin platforms.* Experience with vector databases, embeddings, semantic search, or RAG.* Experience with streaming data platforms such as Kafka, Pub/Sub, Flink, or Spark Streaming.* Experience supporting closed-loop automation, predictive assurance, or self-healing network use cases.* Experience working with OSS systems, inventory platforms, assurance systems ...

data architecture, including data modelling, integration patterns, and modern analytics architectures Experience building and optimising data pipelines using SQL, Python, and/or Spark Knowledge of AI and advanced analytics on Azure, including Azure Machine Learning, Cognitive Services, or Fabric AI capabilities Experience integrating AI-driven insights (e.g. predictive ...

Advanced experience operating Delta tables at scale, covering transaction semantics, schema evolution, partitioning, and compaction, alongside highly optimised analytical query execution using DuckDB or Apache Spark. Production-grade relational database expertise, particularly PostgreSQL (query tuning, indexing, partitioning, replication, and schema design across OLTP and analytics). Strong KDB experience ...

Server, Oracle, Snowflake, Databricks).Experience with data integration (ETL/ELT, APIs).Familiarity with cloud data platforms (AWS, Azure, GCP) and big data (Hadoop, Spark, Kafka) a plus. Domain Knowledge: Exceptional understanding of the Funds business lifecycle, financial instruments, market data, and investment operations. In-depth knowledge of regulatory ...

Stock Exchange. With 3,000 employees and 32 offices in 12 countries we’re a business with lots of opportunity for people with talent, spark and lots of ambition. If you want to build a great career with a company that prioritises strong values – such as integrity and courage ...

GCP. MSc or equivalent experience in Data Science, Statistics, Mathematics, Computer Science, Artificial Intelligence, Physics, Engineering or a related quantitative discipline. Experience with Spark or distributed data processing frameworks. Experience preparing data pipelines or analytical datasets to support machine learning workloads. Awareness of data engineering, data architecture, data governance ...

with Microsoft Azure a plus: Azure SQL Database, Analysis Services, Databricks, Data Lake, Logic Apps and Data Factory Understanding of Big Data technologies (Hadoop, Spark) Able to create rich visualisations that appropriately represent the underlying datasets. Review and align the reporting attributes against the Enterprise and conceptual data models ...

this role leads the engineering of cloud-native data services for the firm's strategic platform, driving the migration to Databricks and delivering scalable Spark/Scala solutions on AWS. The overall objective of this role is to lead applications systems analysis and programming activities. Proven leadership in building … matching engines, AI/GenAI services and large-scale data platforms. This role will drive transformation of enterprise data capabilities using Databricks, scala/spark and cloud native architectures, ensuring platform is stable, scalable, resilient, secure and AI enabled. As platform landscape evolved towards cloud-native, AI enabled ...