1 to 25 of 113 Apache Spark Jobs in the UK

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 ...

databases utilised in modern AI applications. Strong Python development skills. Data & Infrastructure: Experience with some of the following technologies is highly desirable: Frameworks & Infrastructure: Apache Spark Apache Airflow Kafka Elasticsearch/OpenSearch Databases: PostgreSQL MongoDB Vector databases such as Qdrant, Milvus, or pgvector Python Ecosystem: Pandas Polars ...

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 ...

frameworks, tools and applications that make that data available to other teams and systems.Your primary toolset in your work will be Java microservices, Spark/Scala data processing (also some Flink), Kubernetes and AWS native tooling.What You'll Do: Write highly fault-tolerant Java code within Apache Spark … combined between backend/cloud development and data platform engineering roles5+ years of experience building data platform product(s) or features with (one of) Apache Spark, Flink or Iceberg, or with comparable tools in GCP5+ years of experience programming with Java, Scala or Kotlin.Proven experience utilizing AI technologies ...

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 ...

trusted datasets, performant ETL/ELT pipelines, and well-governed data products. Job responsibilities Design and implement batch and streaming data pipelines using Databricks (Spark), Delta Lake , and orchestrators (e.g., Workflows , Airflow, ADF). Develop and optimize Spark jobs (PySpark/Scala) and SQL transformations for performance, reliability … automation capabilities, to improve the value realized by automation Required qualifications, skills and capabilities Experience with building data pipelines on Databricks and/or Apache Spark in production. Strong coding skills in Python (PySpark) and SQL (Scala a plus). Hands-on experience with Delta Lake (MERGE/ ...

Python, Java or Scala, and SQL. Hands-on experience building and operating large-scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud-native data ...

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 ...

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 ...

standards. Skills Strong experience in SQL and data modeling concepts. Hands-on experience with ETL/ELT development. Proficiency in Python, Scala, or Spark-based data processing. Experience with cloud platforms such as AWS, Azure, or GCP. Knowledge of Data Warehouse and Data Lake architectures. Experience with orchestration tools ...

continuous learning to understand new data management systems Strong proficiency in hands-on development using industry-standard tools and languages (e.g., SQL, Python, Spark, cloud platforms), with a commitment to code quality and delivery excellence Preferred qualifications, capabilities, and skills Hands-on experience with Databricks for scalable data engineering … analytics, and collaborative development, as well as proficiency in managing large datasets using Apache Iceberg for efficient, reliable table management and data lake optimization Experience architecting and implementing enterprise-scale data warehouses on cloud platforms (e.g., AWS, Azure, GCP), including migration from legacy systems Advanced proficiency in designing ...

engineers should be adept at Extract, Transform, Load (ETL) processes. This includes using frameworks such as the Medallion Architecture, as well as tools like Apache Airflow, Fivetran, Azure Data Factory, and Amazon Glue to automate data workflows and ensure data quality. Familiarity with cloud computing services, such … Cloud Platform, is increasingly important. Data engineers often leverage these platforms for scalable data storage and processing capabilities. Knowledge of big data frameworks like Apache Spark, Beam is crucial for handling large datasets and real-time data processing. Understanding data modelling techniques helps data engineers design efficient data ...

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 Reporting ...

modern frameworksWorking knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least oneDeep experience with distributed computing with Apache Spark and knowledge of Spark runtime internalsFamiliarity with CI/CD for production deploymentsWorking knowledge of MLOps, ML/AI models ...

quality and consistency across platforms while complying with governance policies. What You Bring: Core Development Skills: - Proficient in Python and SQL, with experience in Apache Spark. - Strong experience building backend services and APIs. Database Expertise: - Solid understanding of relational databases (SQL Server, PostgreSQL) and distributed NoSQL databases (Cassandra, MongoDB ...

quality and consistency across platforms while complying with governance policies. What You Bring: Core Development Skills: - Proficient in Python and SQL, with experience in Apache Spark. - Strong experience building backend services and APIs. Database Expertise: - Solid understanding of relational databases (SQL Server, PostgreSQL) and distributed NoSQL databases (Cassandra, MongoDB ...

Azure) Experience with: o Data warehousing and lake architectures o ETL/ELT pipeline development o SQL and NoSQL databases o Distributed computing frameworks (Spark, Kinesis etc) o Software development best practices including CI/CD, TDD and version control. o Containerisation tools like Docker or Kubernetes o Experience ...

maintain scalable Databricks pipelines (ETL, streaming, ML workflows). Perform cluster and job performance tuning: optimize cluster sizing, caching, partitioning, and shuffle management. Monitor Spark job metrics, analyze logs, and identify bottlenecks in data throughput or latency. Implement cost-optimization strategies for Databricks jobs and clusters using autoscaling … Databricks REST APIs, Prometheus, or Azure Monitor. Maintain best practices for data engineering performance, testing, and documentation. Technical Skills Required Strong proficiency with Databricks, Apache Spark (SQL, PySpark, Scala), and Delta Lake. Deep understanding of Spark execution plans, shuffle optimization, and data partitioning strategies. Experience tuning ...

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 ...

understand where traditional patterns remain appropriate – and where modern approaches add measurable value. Data Engineering & Platform Understanding: Strong knowledge of distributed processing (e.g. Apache Spark).Familiarity with Hadoop ecosystem components. Working knowledge of SQL and NoSQL technologies. Understanding of ETL/ELT design trade-offs. Awareness of DevOps ...

messaging architectures. Data Platforms & Cloud Technologies Hands-on experience with: Azure Data Lake Databricks Snowflake Delta Lake Azure Synapse Analytics/Microsoft Fabric Spark/PySpark Strong understanding of: Data Lake and Lakehouse architecture Hybrid cloud environments Enterprise integration patterns Modern data formats including Parquet, Avro, and ORC DevOps ...

. Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon). Familiarity with data lake architectures and distributed processing frameworks (e.g., Spark, Hadoop). Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines. Understanding of data governance, security, and compliance frameworks. Exposure ...

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 ...

optimising ETL/ELT pipelines. Strong understanding of Lakehouse, Data Warehouse, and Data Lake architectures. Experience with Azure Data Factory, Azure Synapse, and Apache Spark. Knowledge of data modelling, semantic models, and enterprise reporting solutions. Experience implementing data governance, security, and quality frameworks. Strong understanding of modern data engineering ...

toolsUnderstanding of database architecture (SQL and NoSQL)Experience with cloud technologiesExperience with cloud platformsExperience with CI/CD practicesExperience with big data tools e.g. Spark, Hadoop, NiFiExperience managing direct reports, providing regular guidance and performance feedbackAbility to create delivery plans with estimated timelines for personal and team workloadsExperience supporting ...