1 to 25 of 174 Apache Jobs in England

robust way possible! Diverse training opportunities and social benefits (e.g. UK pension schema) What do you offer? Strong hands-on experience working with modern Big Data technologies such as Apache Spark, Trino, Apache Kafka, Apache Hadoop, Apache HBase, Apache Nifi, Apache Airflow, Opensearch Proficiency in cloud-native technologies such as containerization and Kubernetes Strong More ❯

production issues. Optimize applications for performance and responsiveness. Stay Up to Date with Technology: Keep yourself and the team updated on the latest Python technologies, frameworks, and tools like Apache Spark, Databricks, Apache Pulsar, Apache Airflow, Temporal, and Apache Flink, sharing knowledge and suggesting improvements. Documentation: Contribute to clear and concise documentation for software, processes, and … Experience with cloud platforms like AWS, GCP, or Azure. DevOps Tools: Familiarity with containerization (Docker) and infrastructure automation tools like Terraform or Ansible. Real-time Data Streaming: Experience with Apache Pulsar or similar systems for real-time messaging and stream processing is a plus. Data Engineering: Experience with Apache Spark, Databricks, or similar big data platforms for processing … large datasets, building data pipelines, and machine learning workflows. Workflow Orchestration: Familiarity with tools like Apache Airflow or Temporal for managing workflows and scheduling jobs in distributed systems. Stream Processing: Experience with Apache Flink or other stream processing frameworks is a plus. Desired Skills Asynchronous Programming: Familiarity with asynchronous programming tools like Celery or asyncio. Frontend Knowledge: Exposure More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL More ❯

customer data Continuously improve existing systems, introducing new technologies and methodologies that enhance efficiency, scalability, and cost optimisation Essential Skills for the Senior Data Engineer: Proficient with Databricks and Apache Spark, including performance tuning and advanced concepts such as Delta Lake and streaming Strong programming skills in Python with experience in software engineering principles, version control, unit testing and More ❯

in AWS. Strong expertise with AWS services, including Glue, Redshift, Data Catalog, and large-scale data storage solutions such as data lakes. Proficiency in ETL/ELT tools (e.g. Apache Spark, Airflow, dbt). Skilled in data processing languages such as Python, Java, and SQL. Strong knowledge of data warehousing, data lakes, and data lakehouse architectures. Excellent analytical and More ❯

Azure. AWS experience is considered, however Azure exposure is essential. Data Warehousing: Proven expertise with Snowflake – schema design, performance tuning, data ingestion, and security. Workflow Orchestration: Production experience with Apache Airflow (Prefect, Dagster or similar), including authoring DAGs, scheduling workloads and monitoring pipeline execution. Data Modeling: Strong skills in dbt, including writing modular SQL transformations, building data models, and More ❯

skills We're excited if you have 7+ years of experience delivering multi tier, highly scalable, distributed web applications Experience working with Distributed computing frameworks knowledge: Hive/Hadoop, Apache Spark, Kafka, Airflow Working with programming languages Python , Java, SQL. Working on building ETL (Extraction Transformation and Loading) solution using PySpark Experience in SQL/NoSQL database design Deep More ❯

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 (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

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 (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality More ❯

Linux-based, concurrent, high-throughput, low-latency software systems Experience with pipeline orchestration frameworks (e.g. Airflow, Dagster) Experience with streaming platforms (e.g. Kafka), data lake platforms (e.g. Delta Lake, Apache Iceberg), and relational databases Have a Bachelor or advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or equivalent work experience For more information about DRW's processing activities More ❯

and cloud data platforms (AWS, Azure, or GCP). Proficiency in Python and SQL for data manipulation and transformation. Experience with ETL/ELT development and orchestration tools (e.g., Apache Airflow, dbt, Prefect). Knowledge of data modelling, data warehousing, and lakehouse architectures. Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code. Strong problem-solving skills More ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or More ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS or More ❯

of SQL and Python You have strong hands-on experience of building scalable data pipelines in cloud based environments using tools such as DBT, AWS Glue, AWS Lake Formation, Apache Spark and Amazon Redshift You have a good knowledge of data modelling, ELT design patterns, data governance and security best practices You're collaborative and pragmatic with great communication More ❯

of SQL and Python You have strong hands-on experience of building scalable data pipelines in cloud based environments using tools such as DBT, AWS Glue, AWS Lake Formation, Apache Spark and Amazon Redshift You have a good knowledge of data modelling, ELT design patterns, data governance and security best practices You're collaborative and pragmatic with great communication More ❯

systems. Nice to haves: Experience with NoSQL databases (MongoDB, Cassandra, Redis). Familiarity with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Experience working with AI-driven development tools such as Cursor, Copilot, or More ❯

Development Opportunities Enhanced Maternity & Paternity Charity Volunteer Days Cycle to work scheme And More.. DATA ENGINEER – ESSTENTIAL SKILLS Proven experience building data pipelines using Databricks . Strong understanding of Apache Spark (PySpark or Scala) and Structured Streaming . Experience working with Kafka (MSK) and handling real-time data . Good knowledge of Delta Lake/Delta Live Tables and More ❯

frameworks, and clear documentation within your pipelines Experience in the following areas is not essential but would be beneficial: Data Orchestration Tools: Familiarity with modern workflow management tools like Apache Airflow, Prefect, or Dagster Modern Data Transformation: Experience with dbt (Data Build Tool) for managing the transformation layer of the data warehouse BI Tool Familiarity : An understanding of how More ❯

frameworks, and clear documentation within your pipelines Experience in the following areas is not essential but would be beneficial: Data Orchestration Tools: Familiarity with modern workflow management tools like Apache Airflow, Prefect, or Dagster Modern Data Transformation: Experience with dbt (Data Build Tool) for managing the transformation layer of the data warehouse BI Tool Familiarity : An understanding of how More ❯

and Responsibilities While in this position your duties may include but are not limited to: Support the design, development, and maintenance of scalable data pipelines using tools such as Apache Airflow, dbt, or Azure Data Factory. Learn how to ingest, transform, and load data from a variety of sources, including APIs, databases, and flat files. Assist in the setup More ❯

data warehousing, and big data (Hadoop, Spark). Proficient in Python, Java, or Scala with solid OOP and design pattern understanding. Expertise in ETL tools and orchestration frameworks (Airflow, Apache NiFi). Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their data services. More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines and More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines and More ❯

practices such as testing, version control, and CI/CD Hands-on experience building scalable data pipelines in a modern cloud environment (e.g., dbt, AWS Glue, AWS Lake Formation, Apache Spark, Amazon Redshift) Strong understanding of data modeling, ELT design patterns, data governance, and security best practices Bonus . Experience with reverse ETL tools (e.g., Census) Knowledge of data More ❯