1 to 25 of 53 Apache Spark Jobs in the North of England

United Kingdom 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 analytical and engineering skills to deliver trusted … 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 ...

replay, backfill, recoverability and schema evolution Define and enhance operational telemetry, monitoring and platform observability Streaming & Distributed Data Processing Build and optimise solutions using:Apache Kafka Apache NiFi Apache Spark/PySpark Hadoop ecosystem technologies Hive and large-scale data storage platforms Develop scalable matching, enrichment … interested in engineers who can demonstrate strong expertise across several of the following areas: Core Technical Skills Python development in enterprise environments Apache Spark/PySpark Apache Kafka Apache NiFi Hadoop and Hive Advanced SQL REST API integration and development Data modelling and data lineage Distributed ...

deliver secure, reliable, and scalable services that support critical public sector operations. Key Responsibilities Design, develop, and maintain data pipelines and processing workflows using Apache Spark and Python Build, schedule, and monitor workflow orchestration using Apache Airflow Develop and maintain infrastructure-as-code using Terraform across … sprint planning, refinement, and other agile ceremonies Required Skills & Qualifications Experience with AWS services Experience with Terraform for infrastructure as code Experience with Apache Spark for data processing Experience with Apache Airflow for workflow orchestration Experience with Docker and containerisation Experience building and maintaining CI/ ...

explore new technologies, share knowledge, and contribute to a culture of excellence and innovation. 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 ...

automated deployments, infrastructure management, monitoring, and scaling Coaching and mentoring junior engineers and promoting engineering best practices Skills & Experience: Understanding of data processing using Apache Spark and Apache Airflow for task orchestration Use of Python, SQL, and familiarity with PySpark Understanding of EMR and reviewing output logs ...

engineers where needed. Core Data Engineering Strong programming proficiency in Java (preferred) or Python. Hands-on experience with at least one of: Kafka, Flink, Spark (Flink/Kafka preferred for streaming). Solid understanding of stream processing concepts (e.g., event time, state, backpressure). Understanding of software engineering best ...

with strong Foundry depth). Proven, hands-on experience working with Palantir Foundry in a production environment. Strong proficiency in Python, SQL, PySpark and Spark SQL Experience delivering production pipelines in AWS, Azure, or GCP environments. Solid understanding of data modeling, schema design, metadata management, and governance. Familiarity with ...

solutions are secure, scalable, maintainable, and aligned with organisational standards and governance requirements. Design, build, and optimise data pipelines on Databricks using PySpark and Spark SQL, applying Delta Lake and a medallion/Lakehouse architecture. Implement data validation and reconciliation checks, and automated testing across pipelines to ensure trusted ...

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.We … version control.* **Data Engineering Stack** Experience building pipelines using streaming frameworks, distributed processing engines and relational or analytical storage technologies. Examples include Kafka, Spark, PostgreSQL.* **Orchestration** Experience defining and running data workflows using modern orchestration frameworks. Examples include Airflow, Dagster or Prefect.* **Data Quality and Lineage** Familiarity with tools ...

agreed scope, acting as the key point of escalation for decisions that impact your area of work - Demonstrable experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse ...

agreed scope, acting as the key point of escalation for decisions that impact your area of work - Demonstrable experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse ...

agreed scope, acting as the key point of escalation for decisions that impact your area of work - Demonstrable experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse ...

possess hands‐on experience with one or more of the following technological areas (or their equivalent cloud‐native alternatives): Analytics & Platform Frameworks like Apache Spark or similar cloud-specific services. Transformation & Orchestration tools Database Technologies Libraries & Schema Management Storage Formats: Familiarity managing diverse data types through formats like ...

Automated deployments across environments. Monitoring and logging. Release and configuration management. Production support and incident troubleshooting. Python or another scripting language. AWS certification. Terraform. Apache Airflow/MWAA. Databricks or Spark. Kafka/Kinesis. dbt. Experience working in Agile/Scrum environments. Experience 4+ years of experience in Data ...

programming skills, with experience developing and maintaining data pipelines Familiarity with ETL/ELT technologies and data streaming tools such as Airflow, Azure, SSIS, Spark or Kafka Experience working with databases and data platforms such as PostgreSQL, SQL Server, Oracle, Snowflake or similar technologies Knowledge of data visualisation tools ...

highly desirable but strong Python/PySpark engineers who can learn Foundry quickly are encouraged to apply. Extensive experience with Python and PySpark/Apache Spark. Proven track record designing and delivering scalable data pipelines and data products. Strong SQL and data modelling skills. Experience with modern data architectures ...

maintain SC clearance. Desirable AWS certification at Associate or Professional level Experience with streaming and event‐driven data technologies Experience with technologies such as Spark, Kafka or Databricks Experience delivering data platforms within public sector, defence or other regulated environments Experience working within secure environments and understanding associated security ...

Python and SQL; APIs; test automation; data structures; distributed processing; Git; CI/CD; containers; infrastructure awareness; production debugging and performance optimization. Data engineering: Spark or Databricks, Kafka or equivalent streaming, ETL/ELT, batch and real-time pipelines, data contracts, lineage, cataloguing, quality rules, and scalable cloud storage. ...

analytics and AI/ML at enterprise scale.* Develop and optimise batch and streaming ETL/ELT pipelines using Azure Data Factory, PySpark, SQL, Apache Spark and Airflow, integrated with modern tooling like dbt and Git-based CI/CD.* Implement data cataloguing, lineage tracking and governance frameworks … data engineering, including designing and delivering data lake or lakehouse architectures in an enterprise cloud environment, ideally Microsoft Azure.* Hands-on expertise with Databricks, Spark, PySpark, SQL and core Azure Data Services (Data Lake Storage, Synapse Analytics, Data Factory).* Experience with data governance and cataloguing tools such ...

equivalent apprenticeship/work experience in a subject such as Mathematics, Statistics, Computer Science, or Geography DESIRABLE Exposure to Big Data Analytics (BigQuery, Apache Spark), Parallel Computing (Kubernetes, Databricks), Cloud Engineering (AWS, GCP, Azure), Spatial Query Optimisation, Graph Computing, or Microservices Relevant industry sector knowledge across retail, property ...

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 ...

Lambda, ECS, RDS, S3, SQS, API Gateway, and CloudWatch. Design, develop, and maintain data pipelines and ETL workflows using technologies such as Glue, Spark/PySpark, Kafka, or similar platforms. Implement and maintain Infrastructure as Code (IaC) using Terraform or equivalent tools. Drive observability, monitoring, logging, and operational readiness ...

into business processes and decision-making.**Technical Skills:**Hands-on experience in one or more of the following areas:Programming & Analytics – Python, SQL, R, Spark, machine learning and advanced analyticsCloud & Data Platforms – Microsoft Fabric, Databricks, Snowflake, Azure, AWS and GCPAI Technologies – GenAI frameworks, Agentic AI, vector databases, semantic search ...

into business processes and decision-making. Technical Skills: Hands-on experience in one or more of the following areas: Programming & Analytics – Python, SQL, R, Spark, machine learning and advanced analytics Cloud & Data Platforms – Microsoft Fabric, Databricks, Snowflake, Azure, AWS and GCP AI Technologies – GenAI frameworks, Agentic AI, vector databases ...

modern cloud engineering practices. Wherever you land, you’ll be working with some of the biggest datasets in the UK — using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications. Cloud-native AI engineering and large-scale data platforms, leveraging Google Cloud technologies and modern ...