1 to 25 of 159 Apache Spark Jobs in the UK

Lead Backend Software Engineer – Data Services Federated Data Services | Distributed Systems | Apache Spark | DataFusion | Python | Kubernetes Location: London (2 days per week onsite) Rate: £700–£800 per day (Outside IR35) Duration: Initial 6-month contract with likely extension Overview We're looking for an experienced Lead Backend Software … data services capable of securely querying and processing data across multiple environments. Design high-performance data processing and streaming workflows using technologies such as Apache Spark, Apache DataFusion, or similar distributed query frameworks. Design and implement Kubernetes-based services and containerised workloads. Build secure APIs and backend ...

complex legacy data pipelines into production-grade PySpark Building scalable, reusable data movement frameworks across multiple engineering teams Driving best practice around AWS Glue, Apache Spark and Apache Airflow Designing high-quality testing frameworks covering performance, data quality and reliability Leveraging Agentic AI development tools to improve … consumed We're looking for someone with experience in Staff, Principal or Lead Data Engineering roles Python and expert-level PySpark AWS Glue Apache Spark Apache Airflow Cloud-native Data Engineering architectures Large-scale data pipeline modernisation Building reusable engineering patterns within enterprise environments Data testing, validation ...

focus, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will combine deep Databricks and Apache Spark expertise with strong client engagement skills to shape solutions from early-stage opportunity through delivery. You will lead our Databricks partnership activity … sales by contributing to discovery, solution design, estimates, and compelling client-facing materials. Design and build high-performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data across cloud and on-premises sources and targets. Design and oversee the delivery of secure data warehouses ...

should have specialist experience in one or more of the following technologies Azure Databricks Design and build high-performance data pipelines: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Experience of Databricks ML and Azure … develop predictive models and drive business insights. Proven expertise in Databricks, Apache Spark, and data pipeline development and strong understanding of data warehousing concepts and practices. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks and Azure Data Factory. Azure Data Engineer Associate and Databricks ...

will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise in Databricks, Apache Spark, and Azure to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations. What … which Azure data focused components to use for which purpose. Microsoft certified architect Databricks Design and build high-performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Ability to Design, Build and deploy ...

through large-scale distributed processing, structured storage and Data LakeHouse design, to curated consumption by Data Scientists, Analysts, Engineers and AI/ML platforms. Spark and distributed data processing sit at the heart of this architecture; deep fluency in these domains is essentia l. What You’ll Do:Architectural … Leaders hipDefine and evolve the enterprise data architecture strategy, with a primary focus on Cloud-scale Distributed Data Processing using Apache Spark and PySpark at the core of the platf ormEstablish and maintain architectural artefacts, reference architectures, Architecture Decision Records (ADRs), technical standards, and architecture roadmaps ...

technologies, share knowledge, and contribute to a culture of excellence and innovation. Key responsibilities include: • Design & Build: Develop and optimise data pipelines using Databricks, Apache Spark, and Python. • Develop & Deliver: Create scalable data solutions on AWS leveraging S3, Glue, Lambda, and related services. • Integrate & Automate: Implement ETL processes … Hands-on commercial expertise with Databricks. You should have: • Proven experience as a Data Engineer working with large, complex datasets. • Hands-on expertise with Apache Spark, and SQL. • Strong proficiency in Python (PySpark preferred). • Experience with AWS cloud services including S3, Glue, Lambda, IAM. • Familiarity with ...

designing and delivering modern data platforms, working closely with clients and technical teams to build scalable, secure and high-performing solutions using Databricks, Apache Spark and cloud technologies. Key Responsibilities Design and architect Databricks-based data platforms and solutions. Build scalable data lakehouse and data warehouse architectures. Design … Databricks and modern data platform delivery. Skills & Experience Required 7+ years' experience in Data Architecture or Solution Architecture. Strong commercial experience with Databricks and Apache Spark . Experience delivering enterprise data platforms on AWS, Azure or GCP. Strong understanding of data warehousing, data lakes and lakehouse architectures. Experience ...

designing and delivering modern data platforms, working closely with clients and technical teams to build scalable, secure and high-performing solutions using Databricks, Apache Spark and cloud technologies. You'll also play a key role in pre-sales activities, solution design, and helping to drive strategic Databricks initiatives … Databricks and modern data platform delivery. Skills & Experience Required 7+ years' experience in Data Architecture or Solution Architecture. Strong commercial experience with Databricks and Apache Spark . Experience delivering enterprise data platforms on AWS, Azure or GCP. Strong understanding of data warehousing, data lakes and lakehouse architectures. Experience ...

data lakes, operational data stores, event streaming platforms, and real-time data pipelines. Architect and document solutions using technologies such as Hive, Impala, HBase, Spark, NiFi, Flink, Kafka, and equivalent AWS services. Design Kafka-based streaming applications, including event ingestion, topic design, consumer patterns, error handling, replay, scalability …/CDP or equivalent big data platforms. Strong demonstrable experience with some of the distributed data technologies (if not all) such as: HBase Spark NiFi Kafka Flink Hive Impala Experience designing and delivering large-scale data ingestion, transformation, storage, and consumption patterns. Experience with Kafka consumer architecture, including consumer ...

domain-driven approaches CI/CD for data pipelines, version control discipline, infrastructure-as-code basics (Terraform) Streaming and big data exposure (Kafka, Kinesis, Spark, Flink) is a plus Data quality and observability tooling (Great Expectations, Monte Carlo, Soda, dbt tests) is a plus Engineering & Soft Skills: Strong software ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

considering: We are looking for an experienced AWS Databricks Engineer with strong hands-on expertise in Databricks, AWS cloud services, PySpark, Spark SQL, Delta Lake, Python, SQL, and data engineering. The candidate will be responsible for designing, developing, optimizing, and supporting scalable data pipelines and Lakehouse solutions … forums, architecture review boards, design authority meetings, and client stakeholder workshops. Your Skills: Strong hands-on experience with Databricks on AWS. Strong experience with Apache Spark/PySpark. Excellent programming skills in Python. Strong SQL skills including complex queries, joins, CTEs, window functions, and query optimization. AWS Secrets ...