1 to 25 of 51 Remote/Hybrid Apache Spark Jobs in the UK excluding London

Apache Spark Python AWS Cloud Data Pipelines A hands-on data engineering role within a large-scale cloud data programme, responsible for building, maintaining, and troubleshooting data pipelines using Apache Spark, PySpark, Apache Airflow, and a broad suite of AWS services. You will apply strong … complex, cloud-based data programme - designing, building, and maintaining data pipelines that process large volumes of data across a modern AWS-native stack. Using Apache Spark and PySpark for distributed data processing, Apache Airflow for orchestration, and a range of AWS services for storage, compute, and analytics ...

United Kingdom A hands-on data engineering role within a large-scale cloud data programme, responsible for building, maintaining, and troubleshooting data pipelines using Apache Spark, PySpark, Apache Airflow, and a broad suite of AWS services. You will apply strong analytical and engineering skills to deliver trusted … complex, cloud-based data programme - designing, building, and maintaining data pipelines that process large volumes of data across a modern AWS-native stack. Using Apache Spark and PySpark for distributed data processing, Apache Airflow for orchestration, and a range of AWS services for storage, compute, and analytics ...

data processing. In this role, you will architect and maintain production-grade data products and APIs, leveraging technologies such as Java/Scala, SQL, Spark, Airflow, and Kubernetes to deliver reliable, high-performance solutions. You will collaborate with cross-functional partners across Finance, Accounting, and Analytics to translate complex … efficient code, ensuring adherence to best practices through code reviews Big Data Engineering Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow Optimise data storage, retrieval, and processing systems to ensure reliability, scalability, and performance Develop and fine-tune complex queries ...

analytics, reporting, AI/ML, and data-driven decision making across the organization. The ideal candidate possesses strong expertise in modern data engineering practices, Apache Spark, cloud-based data platforms, and lakehouse architectures. As a senior individual contributor, the candidate will provide technical leadership, mentor junior engineers, drive … business stakeholders to deliver trusted, scalable, and analytics-ready data products. Key responsibilities Design, develop, and maintain scalable batch and streaming data pipelines using Apache Spark, cloud-native technologies, and modern data platforms. Build and optimize ETL/ELT frameworks to ingest, transform, validate, and curate data from ...

application components, microservices, and data integration layers to support high-throughput regulatory reporting. Big Data Processing: Develop and optimize distributed data processing jobs using Apache Spark, Hadoop, and Hive to aggregate and transform large-scale financial datasets. Real-Time Streaming: Build and maintain real-time data ingestion … streaming pipelines using Apache Kafka. Database Management: Design and optimize data models in MongoDB and relational databases, ensuring high performance for complex queries and data storage. Agile Execution: Drive sprint planning, task estimation, and daily progress within an Agile/Scrum framework to ensure timely delivery of project milestones. ...

Senior Data Engineer (Databricks) - London (Hybrid) - Up to £85,000 Databricks - Apache Spark - Delta Lake - Python - SQL - Azure We're partnering with a fast-growing technology business that's investing heavily in its data platform and engineering capability. This is an opportunity to join a highly collaborative team … progression within a growing technology business. Key Experience Required 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 ...

Modern data platforms: Databricks, Snowflake and cloud-native data services Data architecture: Lakehouse, medallion, data mesh and domain-oriented patterns Data processing: Apache Spark, SQL and distributed processing technologies Data storage: Delta Lake, Apache Iceberg and open table formats Data pipelines: Enterprise-scale ETL/ELT, batch … streaming patterns Transformation and quality: dbt, Great Expectations and equivalent tooling Orchestration: Apache Airflow and cloud-native orchestration services Event streaming: Kafka and cloud-native event-streaming technologies Data modelling: Dimensional, analytical and domain-oriented modelling Data governance: Catalogue, metadata, lineage, quality, security, privacy and access controls Data products ...

data warehouses and data lakes. (Preferred) Experienced in data ingestion, processing, transformation, and delivery using batch, streaming, and real‐time methods. (Preferred) Experience supporting Spark‐based platforms (e.g. EMR, Glue, Databricks) (Preferred) Proficient with DevOps tools and practices (Git, Jenkins, Docker, Kubernetes) as well as ETL frameworks (Apache Spark, Airflow, AWS IoT Analytics/Device Management/Events). (Preferred) Programming expertise in Python, Java, Scala, SQL, Spark, Unix shell scripting, and AWS CLI. (Preferred) Great background in building and managing AWS platforms for analytics and data lake workloads, including application and framework management. (Preferred ...

data warehouses and data lakes. (Preferred) Experienced in data ingestion, processing, transformation, and delivery using batch, streaming, and real‐time methods. (Preferred) Experience supporting Spark‐based platforms (e.g. EMR, Glue, Databricks) (Preferred) Proficient with DevOps tools and practices (Git, Jenkins, Docker, Kubernetes) as well as ETL frameworks (Apache Spark, Airflow, AWS IoT Analytics/Device Management/Events). (Preferred) Programming expertise in Python, Java, Scala, SQL, Spark, Unix shell scripting, and AWS CLI. (Preferred) Great background in building and managing AWS platforms for analytics and data lake workloads, including application and framework management. (Preferred ...

common technical standards and ways of working, and presenting these to the community Here's a snapshot of the technologies that we use: Scala Apache Spark Databricks Apache Parquet Azure Cloud Platform Azure DevOps (Test plans, Backlogs, Pipelines) GIT What we're looking for We'd love ...

maintain scalable data pipelines data lakes and data warehouse solutions on AWS The role focuses on developing high performance data engineering solutions using PySpark Spark Python and AWS services enabling secure reliable and efficient data processing and analytics across enterprise platforms . Hybrid working: The places that you work … unable to work at home 100% of the time. Your Role: Design develop and maintain scalable batch and realtime data pipelines using PySpark Spark Python and AWS services Build and optimize data lakes and data warehouse solutions ensuring data quality security and accessibility Develop reusable productiongrade ETLELT frameworks ...

with the Lead Data Engineer and partnering with data science, analytics and product teams. Key responsibilities * Build and maintain scalable data pipelines using Databricks, Apache Spark and Delta Lake * Develop and optimise batch and streaming workflows for reliability and performance * Contribute to lakehouse architecture and medallion pattern implementation … optimisation opportunities * Translate business requirements into technical solutions * Contribute to documentation and continuous improvement Required experience * Strong experience delivering production grade Databricks pipelines * Strong Spark, Delta Lake and Databricks Workflows experience * Python and SQL proficiency * Experience on Azure data platforms such as Azure Data Factory, ADLS Gen2, Azure DevOps ...

architecture (SQL and NoSQL) Experience with cloud technologies Experience with cloud platforms Experience with CI/CD practices Experience with big data tools e.g. Spark, Hadoop, NiFi Experience managing direct reports, providing regular guidance and performance feedback Ability to create delivery plans with estimated timelines for personal and team ...

architecture (SQL and NoSQL) Experience with cloud technologies Experience with cloud platforms Experience with CI/CD practices Experience with big data tools e.g. Spark, Hadoop, NiFi Experience managing direct reports, providing regular guidance and performance feedback Ability to create delivery plans with estimated timelines for personal and team ...

Skills MUST HAVE: Strong hands-on experience with Quantexa implementation and development. Proven experience building and supporting big data platforms . Advanced knowledge of Apache Spark/PySpark . Strong programming skills in Scala and/or Python . Expertise in SQL and large-scale data modelling. Strong ...

Lead Data Engineer (Databricks) - London (Hybrid) - Up to £110,000 Databricks - Apache Spark - Delta Lake - Python - SQL - Azure We're partnering with a growing technology business investing heavily in its cloud data platform and AI capabilities. This is a senior, hands-on leadership role where … machine learning and large-scale data initiatives. Key Experience Required Proven experience as a Senior or Lead Data Engineer. Deep expertise in Databricks, Spark, Delta Lake, Python and SQL. Experience designing and scaling cloud-based data platforms. Strong knowledge of ETL/ELT, data modelling and distributed processing. Experience ...

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 ...

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 ...

plusWhat it takesMust-Have Skills & ExperienceDeep expertise designing and building scalable data pipelines and data products in cloud environmentsStrong hands-on experience with Databricks, Spark, SQL, and PythonExperience developing and optimizing batch and real-time data processing solutionsStrong understanding of modern data architecture patterns, including Kimball, Data Vault, dimensional ...

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 ...

continuous delivery (CI/CD) pipelines, containerisation, and workflow orchestration. Familiar with ETL/ELT frameworks, and experienced with Big Data Processing Tools (e.g. Spark, Airflow, Hive, etc.) Knowledge of programming languages (e.g. Java, Python, SQL) Hands-on experience with SQL/NoSQL database design. Degree in STEM ...

continuous delivery (CI/CD) pipelines, containerisation, and workflow orchestration. Familiar with ETL/ELT frameworks, and experienced with Big Data Processing Tools (e.g. Spark, Airflow, Hive, etc.) Knowledge of programming languages (e.g. Java, Python, SQL) Hands-on experience with SQL/NoSQL database design. Degree in STEM ...

continuous delivery (CI/CD) pipelines, containerisation, and workflow orchestration. Familiar with ETL/ELT frameworks, and experienced with Big Data Processing Tools (e.g. Spark, Airflow, Hive, etc.) Knowledge of programming languages (e.g. Java, Python, SQL) Hands-on experience with SQL/NoSQL database design. Degree in STEM ...

Analytics, Artificial Intelligence or a related field, or equivalent experience, would be effective, although practical experience is equally valuable."Nice to Have"Azure, Databricks, Apache Spark or comparable cloud and data platforms. Data pipelines, ETL and workflow-orchestration technologies. Machine-learning methods such as forecasting, prediction or classification. ...

data engineering, ETL development or data platform delivery. Strong programming skills in Java or Python. Exposure to modern data technologies such as Kafka, Spark or Flink. Experience working within cloud environments, ideally AWS. Understanding of software engineering principles, version control and CI/CD practices. Familiarity with container technologies ...