1 to 25 of 788 Apache Spark Jobs in London

extract data from diverse sources, transform it into usable formats, and load it into data warehouses, data lakes or lakehouses. Big Data Technologies: Utilize big data technologies such as Spark, Kafka, and Flink for distributed data processing and analytics. Cloud Platforms: Deploy and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP), leveraging … SQL for data manipulation and scripting. Strong understanding of data modelling concepts and techniques, including relational and dimensional modelling. Experience in big data technologies and frameworks such as Databricks, Spark, Kafka, and Flink. Experience in using modern data architectures, such as lakehouse. Experience with CI/CD pipelines, version control systems like Git, and containerization (e.g., Docker). Experience … with ETL tools and technologies such as Apache Airflow, Informatica, or Talend. Strong understanding of data governance and best practices in data management. Experience with cloud platforms and services such as AWS, Azure, or GCP for deploying and managing data solutions. Strong problem-solving and analytical skills with the ability to diagnose and resolve complex data-related issues. SQL More ❯

extract data from diverse sources, transform it into usable formats, and load it into data warehouses, data lakes or lakehouses. Big Data Technologies: Utilize big data technologies such as Spark, Kafka, and Flink for distributed data processing and analytics. Cloud Platforms: Deploy and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP), leveraging … SQL for data manipulation and scripting. Strong understanding of data modelling concepts and techniques, including relational and dimensional modelling. Experience in big data technologies and frameworks such as Databricks, Spark, Kafka, and Flink. Experience in using modern data architectures, such as lakehouse. Experience with CI/CD pipelines and version control systems like Git. Knowledge of ETL tools and … technologies such as Apache Airflow, Informatica, or Talend. Knowledge of data governance and best practices in data management. Familiarity with cloud platforms and services such as AWS, Azure, or GCP for deploying and managing data solutions. Strong problem-solving and analytical skills with the ability to diagnose and resolve complex data-related issues. SQL (for database management and querying More ❯

in at least one of the big 3 cloud ML stacks (AWS, Azure, GCP). Hands-on experience with open-source ETL, and data pipeline orchestration tools such as Apache Airflow and Nifi. Experience with large scale/Big Data technologies, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka. Experience with workflow orchestration tools like Apache Airflow. More ❯

/Scrum environment. Preferred Qualifications: AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect - Associate. Experience with Airflow for workflow orchestration. Exposure to big data frameworks such as Apache Spark, Hadoop, or Presto. Hands-on experience with machine learning pipelines and AI/ML data engineering on AWS. Benefits: Competitive salary and performance-based bonus structure. Join More ❯

In this role, you will be responsible for designing, building, and maintaining robust data pipelines and infrastructure on the Azure cloud platform. You will leverage your expertise in PySpark, Apache Spark, and Apache Airflow to process and orchestrate large-scale data workloads, ensuring data quality, efficiency, and scalability. If you have a passion for data engineering and … significant impact, we encourage you to apply! Job Responsibilities ETL/ELT Pipeline Development: Design, develop, and optimize efficient and scalable ETL/ELT pipelines using Python, PySpark, and Apache Airflow. Implement batch and real-time data processing solutions using Apache Spark. Ensure data quality, governance, and security throughout the data lifecycle. Cloud Data Engineering: Manage and optimize … effectiveness. Implement and maintain CI/CD pipelines for data workflows to ensure smooth and reliable deployments. Big Data & Analytics: Develop and optimize large-scale data processing pipelines using Apache Spark and PySpark. Implement data partitioning, caching, and performance tuning techniques to enhance Spark-based workloads. Work with diverse data formats (structured and unstructured) to support advanced More ❯

team working with our Central Government client on a contract basis. This role requires a deep understanding of data engineering best practices, strong hands-on experience with AWS, Azure, Apache Spark, data warehousing, database modelling and SQL. You’ll play a critical role in designing, building, and maintaining our data infrastructure to support scalable, high-performance data pipelines … and analytics platforms. Responsibilities will include: Design, build, and maintain robust, scalable, and secure data pipelines using AWS services and Apache Spark. Develop and optimize data models for reporting and analytics in Redshift and other DWH platforms. Collaborate with Data Scientists, Analysts, and Business Stakeholders to understand data requirements and deliver clean, validated datasets. Monitor, troubleshoot, and optimize ETL … experience with a variety of database technologies including Oracle, Postgres and MSSQLServer; Strong expertise in AWS services including AWS DMS, S3, Lambda, Glue, EMR, Redshift, and IAM. Proficient in Apache Spark (batch and/or streaming) and big data processing. Solid experience with SQL and performance tuning in data warehouse environments. Hands-on experience with Amazon Redshift or More ❯

solutions aligned with business objectives. Key Responsibilities Data Pipeline Development Architect, implement and maintain real-time and batch data pipelines to handle large datasets efficiently. Employ frameworks such as Apache Spark, Databricks, Snowflake or Airflow to automate ingestion, transformation, and delivery. Data Integration & Transformation Work with Data Analysts to understand source-to-target mappings and quality requirements. Build … security measures (RBAC, encryption) and ensure regulatory compliance (GDPR). Document data lineage and recommend improvements for data ownership and stewardship. Qualifications Programming: Python, SQL, Scala, Java. Big Data: Apache Spark, Hadoop, Databricks, Snowflake, etc. Cloud: AWS (Glue, Redshift), Azure (Synapse, Data Factory, Fabric), GCP (BigQuery, Dataflow). Data Modelling & Storage: Relational (PostgreSQL, SQL Server), NoSQL (MongoDB, Cassandra More ❯

exciting and critical challenges to the UK’s digital landscape. This role requires strong expertise in building and managing data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. The successful candidate will design, implement, and maintain scalable, secure data solutions, ensuring compliance with strict security standards and regulations. This is a UK based onsite role with … the option of compressed hours. The Role Will Include Design, develop, and maintain secure and scalable data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. Implement data ingestion, transformation, and integration processes, ensuring data quality and security. Collaborate with data architects and security teams to ensure compliance with security policies and data governance standards. Manage and … experience working as a Data Engineer in secure or regulated environments. Expertise in the Elastic Stack (Elasticsearch, Logstash, Kibana) for data ingestion, transformation, indexing, and visualization. Strong experience with Apache NiFi for building and managing complex data flows and integration processes. Knowledge of security practices for handling sensitive data, including encryption, anonymization, and access control. Familiarity with data governance More ❯

Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure … Databricks Implementation: Work extensively with Azure Databricks Unity Catalog, including Delta Lake, Spark SQL, and other relevant services. Implement best practices for Databricks development and deployment. Optimise Databricks workloads for performance and cost. Need to program using the languages such as SQL, Python, R, YAML and JavaScript Data Integration: Integrate data from various sources, including relational databases, APIs, and … best practices. Essential Skills & Experience: 10+ years of experience in data engineering, with at least 3+ years of hands-on experience with Azure Databricks. Strong proficiency in Python and Spark (PySpark) or Scala. Deep understanding of data warehousing principles, data modelling techniques, and data integration patterns. Extensive experience with Azure data services, including Azure Data Factory, Azure Blob Storage More ❯

Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure … Databricks Implementation: Work extensively with Azure Databricks Unity Catalog, including Delta Lake, Spark SQL, and other relevant services. Implement best practices for Databricks development and deployment. Optimise Databricks workloads for performance and cost. Need to program using the languages such as SQL, Python, R, YAML and JavaScript Data Integration: Integrate data from various sources, including relational databases, APIs, and … best practices. Essential Skills & Experience: 10+ years of experience in data engineering, with at least 3+ years of hands-on experience with Azure Databricks. Strong proficiency in Python and Spark (PySpark) or Scala. Deep understanding of data warehousing principles, data modelling techniques, and data integration patterns. Extensive experience with Azure data services, including Azure Data Factory, Azure Blob Storage More ❯

and Workflows, Cluster Management, Catalog Design and Maintenance, Apps, Hive Metastore Management, Network Management, Delta Sharing, Dashboards, and Alerts. Proven experience working with big data technologies, i.e., Databricks and Apache Spark. Proven experience working with Azure data platform services, including Storage, ADLS Gen2, Azure Functions, Kubernetes. Background in cloud platforms and data architectures, such as Corporate DataLake, Medallion Architecture … Platform, Event-driven architecture. Proven experience of ETL/ELT, including Lakehouse, Pipeline Design, Batch/Stream processing. Strong working knowledge of programming languages, including Python, SQL, PowerShell, PySpark, Spark SQL. Good working knowledge of data warehouse and data mart architectures. Good experience in Data Governance, including Unity Catalog, Metadata Management, Data Lineage, Quality Checks, Master Data Management. Experience More ❯

technologies to create and maintain data assets and reports for business insights. Assist in engineering and managing data models and pipelines within a cloud environment, utilizing technologies like Databricks, Spark, Delta Lake, and SQL. Contribute to the maintenance and enhancement of our progressive tech stack, which includes Python, PySpark, Logic Apps, Azure Functions, ADLS, Django, and ReactJs. Support the … technologies to create and maintain data assets and reports for business insights. Assist in engineering and managing data models and pipelines within a cloud environment, utilizing technologies like Databricks, Spark, Delta Lake, and SQL. Contribute to the maintenance and enhancement of our progressive tech stack, which includes Python, PySpark, Logic Apps, Azure Functions, ADLS, Django, and ReactJs. Support the … environment and various platforms, including Azure, SQL Server. NoSQL databases is good to have. Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience with DataOps practices and tools, including CI/CD for data pipelines. Experience in medallion data architecture and other similar data modelling approaches. Experience with data More ❯

technologies to create and maintain data assets and reports for business insights. Assist in engineering and managing data models and pipelines within a cloud environment, utilizing technologies like Databricks, Spark, Delta Lake, and SQL. Contribute to the maintenance and enhancement of our progressive tech stack, which includes Python, PySpark, Logic Apps, Azure Functions, ADLS, Django, and ReactJs. Support the … environment and various platforms, including Azure, SQL Server. NoSQL databases is good to have. Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience with DataOps practices and tools, including CI/CD for data pipelines. Experience in medallion data architecture and other similar data modelling approaches. Experience with data More ❯

technologies to create and maintain data assets and reports for business insights. Assist in engineering and managing data models and pipelines within a cloud environment, utilizing technologies like Databricks, Spark, Delta Lake, and SQL. Contribute to the maintenance and enhancement of our progressive tech stack, which includes Python, PySpark, Logic Apps, Azure Functions, ADLS, Django, and ReactJs. Support the … environment and various platforms, including Azure, SQL Server. NoSQL databases is good to have. Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience with DataOps practices and tools, including CI/CD for data pipelines. Experience in medallion data architecture and other similar data modelling approaches. Experience with data More ❯

and real-time streaming. Knowledge of developing and processing full and incremental loads. Experience of automated loads using Databricks workflows and Jobs Expertise in Azure Databricks, including Delta Lake, Spark optimizations, and MLflow. Strong experience with Azure Data Factory (ADF) for data integration and orchestration. Hands-on experience with Azure DevOps, including pipelines, repos, and infrastructure as code (IaC … including monitoring, logging, and cost management. Knowledge of data security, compliance, and governance in Azure, including Azure Active Directory (AAD), RBAC, and encryption. Experience working with big data technologies (Spark, Python, Scala, SQL). Strong problem-solving and troubleshooting skills. Excellent communication skills with the ability to collaborate with cross-functional teams to understand requirements, data solutions, data models More ❯

and real-time streaming. Knowledge of developing and processing full and incremental loads. Experience of automated loads using Databricks workflows and Jobs Expertise in Azure Databricks, including Delta Lake, Spark optimizations, and MLflow. Strong experience with Azure Data Factory (ADF) for data integration and orchestration. Hands-on experience with Azure DevOps, including pipelines, repos, and infrastructure as code (IaC … including monitoring, logging, and cost management. Knowledge of data security, compliance, and governance in Azure, including Azure Active Directory (AAD), RBAC, and encryption. Experience working with big data technologies (Spark, Python, Scala, SQL). Strong problem-solving and troubleshooting skills. Excellent communication skills with the ability to collaborate with cross-functional teams to understand requirements, data solutions, data models More ❯

Python, Scala, or Java Experience with cloud data platforms such as GCP (BigQuery, Dataflow) or Azure (Data Factory, Synapse) Expert in SQL, MongoDB and distributed data systems such as Spark, Databricks or Kafka Familiarity with data warehousing concepts and tools (e.g. Snowflake) Experience with CI/CD pipelines, containerization (Docker), and infrastructure-as-code (Terraform, CloudFormation) Strong understanding of More ❯

Python, Scala, or Java Experience with cloud data platforms such as GCP (BigQuery, Dataflow) or Azure (Data Factory, Synapse) Expert in SQL, MongoDB and distributed data systems such as Spark, Databricks or Kafka Familiarity with data warehousing concepts and tools (e.g. Snowflake) Experience with CI/CD pipelines, containerization (Docker), and infrastructure-as-code (Terraform, CloudFormation) Strong understanding of More ❯

Automate data quality and observability checks, proactively surfacing issues. Qualifications We seek experienced Data Engineers passionate about data, eager to implement best practices in a dynamic environment. Proficiency in Spark/PySpark, Azure data technologies, Python or Scala, SQL. Experience with testing frameworks like pytest or ScalaTest. Knowledge of open table formats such as Delta, Iceberg, or Apache … and agile methodologies like Scrum or Kanban. Nice to have skills: Experience in retail or e-commerce. Knowledge of Big Data and Distributed Computing. Familiarity with streaming technologies like Spark Structured Streaming or Apache Flink. Additional programming skills in PowerShell or Bash. Understanding of Databricks Ecosystem components. Experience with Data Observability or Data Quality frameworks. Additional Information What More ❯

Job Accountabilities ·Develop robust, scalable data pipelines to serve the easyJet analyst and data science community. ·Highly competent hands-on experience with relevant Data Engineering technologies, such as Databricks, Spark, Spark API, Python, SQL Server, Scala. ·Work with data scientists, machine learning engineers and DevOps engineers to develop, develop and deploymachine learning models and algorithms aimed at addressing … Job Accountabilities ·Develop robust, scalable data pipelines to serve the easyJet analyst and data science community. ·Highly competent hands-on experience with relevant Data Engineering technologies, such as Databricks, Spark, Spark API, Python, SQL Server, Scala. ·Work with data scientists, machine learning engineers and DevOps engineers to develop, develop and deploymachine learning models and algorithms aimed at addressing … indexing, partitioning. ·Hands-on IaC development experience with Terraform or CloudFormation. ·Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. ·Significant experience with Apache Spark or any other distributed data programming frameworks (, Hadoop, Beam) ·Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. ·Experience with data quality and More ❯

Kubernetes , and serverless architectures. Distributed Systems : Strong understanding of distributed systems, microservices architectures, and the challenges of building high-throughput, low-latency systems. Hands-on experience with tools like Apache Kafka , RabbitMQ , Apache Pulsar , and other messaging systems for real-time data streaming. DevOps and Infrastructure Automation : Expertise in DevOps principles, infrastructure-as-code, and automation tools such … Kubernetes . Experience with building, maintaining, and optimizing CI/CD pipelines. Big Data & Data Engineering : Strong background in processing large datasets and building data pipelines using platforms like Apache Spark , Databricks , Apache Flink , or similar big data tools. Experience with batch and stream processing. Security : In-depth knowledge of security practices in cloud environments, including identity More ❯

retail, infrastructure and telco. The ideal candidate with have expertise in some of the following: Python, SQL, Scala, and Java for data engineering. Strong experience with big data tools (Apache Spark, Hadoop, Databricks, Dask) and cloud platforms (AWS, Azure, GCP). Proficient in data modelling (relational, NoSQL, dimensional) and DevOps automation (Docker, Kubernetes, Terraform, CI/CD). More ❯

AWS or Azure) for deploying and scaling data systems. Highly desired experience with Azure, particularly Lakehouse and Eventhouse architectures. Experience with relevant infrastructure and tools including NATS, Power BI, Apache Spark/Databricks, and PySpark. Hands-on experience with data warehousing methodologies and optimization libraries (e.g., OR-Tools). Experience with log analysis, forensic debugging, and system performance More ❯

industries) on some of our most complex projects - individually or by leading small delivery teams. Our projects are fast-paced, typically 2 to 4 months long, and primarily use Apache Spark/Databricks on AWS/Azure. You will manage customer relationships either alone or with a Project Manager, and support our pre-sales, mentoring, and hiring efforts. More ❯

have framework experience within either Flask, Tornado or Django, Docker Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc Data acquisition and development of data sets and improving data quality Preparing data for predictive and prescriptive modelling Hands on coding experience, such as More ❯