1 to 25 of 224 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 ...

design, implement, and optimize enterprise-scale data platforms using the Databricks Lakehouse Platform . The ideal candidate will have deep expertise in Databricks architecture, Apache Spark, Delta Lake, data engineering, cloud platforms, and enterprise data solutions. Key Responsibilities Design and architect Databricks Lakehouse solutions for large-scaleenterprise data … Databricks implementation, including architecture, development, deployment, and optimization. Define Databricks workspace architecture, clusterstrategies, security models, and operational standards. Design and developscalable data pipelinesusing Databricks, Apache Spark, PySpark, SQL, andDelta Lake . Implement data ingestionframeworks supporting batchand real-timedata processing. Design Delta Lake architectures including: Delta tables Medallion architecture ...

platform at scale, ideally in a consumer or marketplace environment. Deep understanding of distributed systems and modern data ecosystems — including extensive experience with Databricks, Apache Spark, Apache Kafka, Apache Flink, Apache Beam and DBT. Demonstrated success in designing, building, and operating data platforms at scale ...

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 … data is governed, managed and consumed Qualifications Staff, Principal or Lead Data Engineering roles Expertise in Python and PySpark Experience with AWS Glue, Apache Spark and Apache Airflow Cloud‐native data engineering architectures Large‐scale data pipeline modernisation Building reusable engineering patterns within enterprise environments Data testing ...

intersection of consulting, technology, innovation, and strategic alliances and you will bring deep expertise in the Databricks Data Intelligence Platform, Lakehouse architecture, Delta Lake, Apache Spark, Unity Catalog, MLflow, Mosaic AI, data engineering, machine learning, GenAI and cloud-native delivery. As a key leader within our AI & Data … translate business needs into Databricks-led solution designs, build prototypes and proof points. Shape end-to-end solutions using Databricks Intelligence Platform, Delta Lake, Apache Spark, Unity Catalog, Databricks Workflows, Delta Live Tables/Lakeflow-style pipelines, MLflow, Feature Store, Model Serving and Mosaic AI capabilities. Build, lead ...

intersection of consulting, technology, innovation, and strategic alliances and you will bring deep expertise in the Databricks Data Intelligence Platform, Lakehouse architecture, Delta Lake, Apache Spark, Unity Catalog, MLflow, Mosaic AI, data engineering, machine learning, GenAI and cloud-native delivery. As a key leader within our AI & Data … translate business needs into Databricks-led solution designs, build prototypes and proof points. • Shape end-to-end solutions using Databricks Intelligence Platform, Delta Lake, Apache Spark, Unity Catalog, Databricks Workflows, Delta Live Tables/Lakeflow-style pipelines, MLflow, Feature Store, Model Serving and Mosaic AI capabilities. Team Leadership ...

root‐cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark . Working knowledge of common data formats such as JSON , Avro and Parquet . Technology Environment The role will involve working with … should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, Kafka Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ Engineering and deployment: CI/CD tooling, containerised ...

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 ...

related disciplines within enterprise environments 4+ years of hands‐on experience designing and implementing solutions on the Databricks Lakehouse Platform Strong expertise in Apache Spark, SQL, Python, Delta Lake, and modern data engineering practices Experience building and optimizing Extract, Transform, Load and Extract, Load, Transform data pipelines … solutions on the Databricks Lakehouse Platform. Design and implement scalable data and analytics solutions leveraging Databricks technologies Build, maintain, and optimize data pipelines using Apache Spark, SQL, Python, and Delta Lake Develop governed datasets and data products that support reporting, analytics, and artificial intelligence initiatives Partner with business ...

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 to produce platform products used by our customers to query our event pipelines/ingestion for insight into active threat trends and related analytics* Design, develop, and maintain ultra-high-scale data platforms that process petabytes of data* Participate in technical reviews of our products and help ...

data processing solutions using BigQuery, Pub/Sub, Dataflow and Dataproc Experience developing end‐to‐end solutions using batch and streaming frameworks such as Apache Spark and Apache Beam. Expert understanding of when to use a range of data storage technologies including relational/non‐relational, document ...

Document stores).Hands-on experience building, scaling, and shipping large-scale data platforms in production.Deep practical experience with distributed data processing frameworks (e.g., Apache Spark, Flink, Hadoop).Strong expertise in message brokers and event streaming platforms (e.g., Apache Kafka, Kinesis).End-to-end exposure to data pipeline … lifecycle development, including extensive experience with workflow orchestration tools (e.g., Apache Airflow, Dagster).Hands-on expertise with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lake architectures (e.g., Databricks, Delta Lake, Apache Iceberg).Advanced SQL skills and proficiency in Python. Strong background in modern software development practices ...

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/ ...

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/ ...

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 tools ...

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 ...

strategic planningRequired Skills & ExperienceTechnical SkillsStrong proficiency in SQL and data modellingExcellent programming skills in Python, Scala, or JavaHands-on experience with distributed data frameworks (Spark, Hadoop)Experience with data pipelines and ETL toolsExpertise in at least one cloud platform:Azure (Synapse, Data Factory, Databricks)AWS (S3, Glue, Redshift, Lambda ...

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 ...

practitioner, you will collaborate with architects, engineers, and analysts to deliver secure, scalable, and high-performing migration solutions, leveraging technologies such as AWS Glue, Apache Iceberg, Python/PySpark, SQL, and YAML-based configurations.You will thrive in a collaborative, client-facing environment, with a passion for solving complex data … target cloud architecturesData Pipeline Testing & Validation (Core Focus)Test end-to-end ETL data solutions running on AWS services, including AWS Glue and Apache IcebergValidate data feed pipeline migrations transitioning to new AWS Data Lakehouse architecturesTest pipelines underpinned by:AI ETL acceleratorsPython/PySpark transformationsSQL-based logicYAML configuration-driven ...