1 to 25 of 33 Apache Spark Jobs in the North of England

data-based insights, collaborating closely with stakeholders. Passionately discover hidden solutions in large datasets to enhance business outcomes. Design, develop, and maintain data processing pipelines using Cloudera technologies, including Apache Hadoop, Apache Spark, Apache Hive, and Python. Collaborate with data engineers and scientists to translate data requirements into technical specifications. Develop and maintain frameworks for efficient More ❯

focused data team responsible for building and optimising scalable, production-grade data pipelines and infrastructure. Key Responsibilities: Design and implement robust, scalable ETL/ELT pipelines using Databricks and Apache Spark Ingest, transform, and manage large volumes of data from diverse sources Collaborate with analysts, data scientists, and business stakeholders to deliver clean, accessible datasets Ensure high performance … practices Work with cloud-native tools and services (preferably Azure ) Required Skills & Experience: Proven experience as a Data Engineer on cloud-based projects Strong hands-on skills with Databricks , Apache Spark , and Python or Scala Proficient in SQL and working with large-scale data environments Experience with Delta Lake , Azure Data Lake , or similar technologies Familiarity with version More ❯

focused data team responsible for building and optimising scalable, production-grade data pipelines and infrastructure. Key Responsibilities: Design and implement robust, scalable ETL/ELT pipelines using Databricks and Apache Spark Ingest, transform, and manage large volumes of data from diverse sources Collaborate with analysts, data scientists, and business stakeholders to deliver clean, accessible datasets Ensure high performance … practices Work with cloud-native tools and services (preferably Azure ) Required Skills & Experience: Proven experience as a Data Engineer on cloud-based projects Strong hands-on skills with Databricks , Apache Spark , and Python or Scala Proficient in SQL and working with large-scale data environments Experience with Delta Lake , Azure Data Lake , or similar technologies Familiarity with version More ❯

able to work across full data cycle. • Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD • Coding experience in Apache Spark, Iceberg or Python (Pandas) • Experience in change and release management. • Experience in Database Warehouse design and data modelling • Experience managing Data Migration projects. • Cloud data platform development … the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB • Good experience with DBT, Apache Iceberg, Docker, Microsoft BI stack (nice to have) • Experience in data warehouse design (Kimball and lake house, medallion and data vault) is a definite preference as is knowledge of … other data tools and programming languages such as Python & Spark and Strong SQL experience. • Experience is building Data lake and building CI/CD data pipelines • A candidate is expected to understand and can demonstrate experience across the delivery lifecycle and understand both Agile and Waterfall methods and when to apply these. Experience: This position requires several years of More ❯

management and associated tools such as Git/Bitbucket. Experience in the use of CI/CD tools such as Jenkins or an understanding of their role. Experience with Apache Spark or Hadoop. Experience in building data pipelines. Experience of designing warehouses, ETL pipelines and data modelling. Good knowledge in designing, building, using, and maintaining REST APIs. Good More ❯

knowledge of Kafka , Confluent , and event-driven architecture Hands-on experience with Databricks , Unity Catalog , and Lakehouse architectures Strong architectural understanding across AWS, Azure, GCP , and Snowflake Familiarity with Apache Spark, SQL/NoSQL databases, and programming (Python, R, Java) Knowledge of data visualisation, DevOps principles, and ML/AI integration into data architectures Strong grasp of data More ❯

Strong experience in Infrastructure as Code (IaC) and deploying infrastructure across environments Managing cloud infrastructure with a DevOps approach Handling and transforming various data types (JSON, CSV, etc.) using Apache Spark, Databricks, or Hadoop Understanding modern data system architectures (Data Warehouse, Data Lakes, Data Meshes) and their use cases Creating data pipelines on cloud platforms with error handling More ❯

Strong experience in Infrastructure as Code (IaC) and deploying infrastructure across environments Managing cloud infrastructure with a DevOps approach Handling and transforming various data types (JSON, CSV, etc.) using Apache Spark, Databricks, or Hadoop Understanding modern data system architectures (Data Warehouse, Data Lakes, Data Meshes) and their use cases Creating data pipelines on cloud platforms with error handling More ❯

their growth and development Apply agile methodologies (Scrum, pair programming, etc.) to deliver value iteratively Essential Skills & Experience Extensive hands-on experience with programming languages such as Python, Scala, Spark, and SQL Strong background in building and maintaining data pipelines and infrastructure In-depth knowledge of cloud platforms and native cloud services (e.g., AWS, Azure, or GCP) Familiarity with More ❯

experience working as a Software Engineer on large software applications Proficient in many of the following technologies - Python, REST, PyTorch, TensorFlow, Docker, FastAPI, Selenium, React, TypeScript, Redux, GraphQL, Kafka, Apache Spark. Experience working with one or more of the following database systems - DynamoDB, DocumentDB, MongoDB Demonstrated expertise in unit testing and tools - JUnit, Mockito, PyTest, Selenium. Strong working knowledge More ❯

best practices for data security and compliance. Collaborate with stakeholders and external partners. Skills & Experience: Strong experience with AWS data technologies (e.g., S3, Redshift, Lambda). Proficient in Python, Apache Spark, and SQL. Experience in data warehouse design and data migration projects. Cloud data platform development and deployment. Expertise across data warehouse and ETL/ELT development in More ❯

requirements. In order to secure one of these Senior Data Engineer roles you must be able to demonstrate the following experience: Experience in prominent languages such as Python, Scala, Spark, SQL. Good experience in using Databricks Experience working with any database technologies from an application programming perspective - Oracle, MySQL, Mongo DB etc. Experience with the design, build and maintenance More ❯

of a forward-thinking company where data is central to strategic decision-making. We’re looking for someone who brings hands-on experience in streaming data architectures, particularly with Apache Kafka and Confluent Cloud, and is eager to shape the future of scalable, real-time data pipelines. You’ll work closely with both the core Data Engineering team and … the Data Science function, bridging the gap between model development and production-grade data infrastructure. What You’ll Do: Design, build, and maintain real-time data streaming pipelines using Apache Kafka and Confluent Cloud. Architect and implement robust, scalable data ingestion frameworks for batch and streaming use cases. Collaborate with stakeholders to deliver high-quality, reliable datasets to live … experience in a Data Engineering or related role. Strong experience with streaming technologies such as Kafka, Kafka Streams, and/or Confluent Cloud (must-have). Solid knowledge of Apache Spark and Databricks. Proficiency in Python for data processing and automation. Familiarity with NoSQL technologies (e.g., MongoDB, Cassandra, or DynamoDB). Exposure to machine learning pipelines or close More ❯

to support data needs Optimise data storage and retrieval for performance Work with batch and real-time processing frameworks Implement and manage ETL processes Use tools like Python, SQL, Spark, Airflow, Kafka, dbt, Snowflake, Redshift, BigQuery Requirements Bachelors degree in Computer Science, Engineering, or a related field 1+ year in a Data Engineer or similar role Proficiency in SQL More ❯

control providers, preferably Git Proven to be an excellent communicator with a clear passion for data & analytics. Deep engineering and database skills in SQL, Server Azure Synapse, Data factory, spark compute and Databricks technologies. Experience of developing coding standards and deliver methods that others follow. Experience of testing techniques, tools and approaches. Extensive experience of the full data lifecycle. More ❯

developing & deploying scalable backend systems. Familiarity with CICD, containerisation, deployment technologies & cloud platforms (Jenkins, Kubernetes, Docker, AWS) or Familiarity with Big Data and Machine Learning technologies (NumPy, PyTorch, TensorFlow, Spark). Excellent communication, collaboration & problem solving skills, ideally with some experience in agile ways of working. Security clearance: You must be able to gain and maintain the highest level More ❯

Research/Statistics or other quantitative fields. Experience in NLP, image processing and/or recommendation systems. Hands on experience in data engineering, working with big data framework like Spark/Hadoop. Experience in data science for e-commerce and/or OTA. We welcome both local and international applications for this role. Full visa sponsorship and relocation assistance More ❯

on Databricks Data Platform & Optimization Design and optimize Databricks clusters for performance, cost management, and resource utilization Implement medallion architecture (Bronze, Silver, Gold) for data processing and transformation Optimize Spark jobs and queries for maximum performance and cost efficiency Monitor and troubleshoot data pipeline performance issues Collaboration & Best Practices Work closely with data scientists, analysts, and business stakeholders to … Airflow, or similar) Understanding of Azure security best practices, RBAC, and data encryption Streaming & Real-Time Processing Knowledge of real-time data processing using Azure Event Hubs, Kafka, and Spark Streaming Experience with event-driven architectures and streaming data pipelines Data Governance Understanding of data governance frameworks, Unity Catalog, and data quality practices Experience with data lineage, cataloguing, and More ❯

the ability to pivot strategies in response to innovative technologies, insights, or regulatory developments. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Snowflake, Spark). Strong communication skills, with the ability to distill complex data concepts into clear messages for non-technical stakeholders. Excellent stakeholder management and cross-functional collaboration skills, with the More ❯

and listed on the London 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 - where our people always pull More ❯

Bermuda and listed on the London Stock Exchange. With 3,000 employees and 32 offices in 12 countries were 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 where our people always pull More ❯

Disaster recovery process/tools Experience in troubleshooting and problem resolution Experience in System Integration Knowledge of the following: Hadoop, Flume, Sqoop, Map Reduce, Hive/Impala, Hbase, Kafka, Spark Streaming Experience of ETL tools incorporating Big Data Shell Scripting, Python Beneficial Skills: Understanding of: LAN, WAN, VPN and SD Networks Hardware and Cabling set-up experience Experience of More ❯

What you will bring Deep technical expertise in at least one data ecosystem (e.g. Oracle, SQL Server, Cloud Data platforms) plus real-time data streaming/processing technologies (Kafka, Spark). Data modelling and governance proficiency, covering conceptual, logical, and physical architectures, metadata management. Cloud data technologies: experience architecting solutions on AWS, Azure, or GCP, optimising cost, performance, and More ❯

key abilities or experience: Deep technical expertise in at least one data ecosystem (e.g. Oracle, SQL Server, Cloud Data platforms) plus real-time data streaming/processing technologies (Kafka, Spark). Data modelling and governance proficiency, covering conceptual, logical, and physical architectures, metadata management. Cloud data technologies: experience architecting solutions on AWS, Azure, or GCP, optimising cost, performance, and More ❯

key abilities or experience: Deep technical expertise in at least one data ecosystem (e.g. Oracle, SQL Server, Cloud Data platforms) plus real-time data streaming/processing technologies (Kafka, Spark). Data modelling and governance proficiency, covering conceptual, logical, and physical architectures, metadata management. Cloud data technologies: experience architecting solutions on AWS, Azure, or GCP, optimising cost, performance, and More ❯