1 to 25 of 116 Apache Spark Jobs in the UK excluding London

culture. Key Responsibilities Design, build, and maintain scalable data solutions to support business objectives. Work with Microsoft Fabric to develop robust data pipelines. Utilise Apache Spark and the Spark API to handle large-scale data processing. Contribute to data strategy, governance, and architecture best practices. Identify and … approaches. Collaborate with cross-functional teams to deliver projects on time . Key Requirements ? Hands-on experience with Microsoft Fabric . ? Strong expertise in Apache Spark and Spark API . ? Knowledge of data architecture, engineering best practices, and governance . ? DP-600 & DP-700 certifications are highly More ❯

years of hands-on experience with big data tools and frameworks. Technical Skills: Proficiency in SQL, Python, and data pipeline tools such as Apache Kafka, Apache Spark, or AWS Glue. Problem-Solving: Strong analytical skills with the ability to troubleshoot and resolve data issues. Communication: Excellent communication More ❯

Databricks. Solid understanding of ETL processes , data modeling, and data warehousing. Familiarity with SQL and relational databases. Knowledge of big data technologies , such as Spark, Hadoop, or Kafka, is a plus. Strong problem-solving skills and the ability to work in a collaborative team environment. Excellent verbal and written More ❯

to the experimentation and development of new ad products at Yelp. Design, build, and maintain efficient data pipelines using large-scale processing tools like Apache Spark to transform ad-related data. Manage high-volume, real-time data streams using Apache Kafka and process them with frameworks like … Apache Flink. Estimate timelines for projects, feature enhancements, and bug fixes. Work with large-scale data storage solutions, including Apache Cassandra and various data lake systems. Collaborate with cross-functional teams, including engineers, product managers and data scientists, to understand business requirements and translate them into effective system … a proactive approach to identifying opportunities and recommending scalable, creative solutions. Exposure to some of the following technologies: Python, AWS Redshift, AWS Athena/Apache Presto, Big Data technologies (e.g S3, Hadoop, Hive, Spark, Flink, Kafka etc), NoSQL systems like Cassandra, DBT is nice to have. What you More ❯

IaC), automation & configuration management • Ansible (plus Puppet, Saltstack), Terraform, CloudFormation • NodeJS, REACT/MaterialUI (plus Angular), Python, JavaScript • Big data processing and analysis, e.g. Apache Hadoop (CDH), Apache Spark • RedHat Enterprise Linux, CentOS, Debian or Ubuntu. • Java 8, Spring framework (preferably Spring boot), AMQP - RabbitMQ, • Open source More ❯

you be doing? Design and implement efficient ETL processes for data extraction, transformation, and loading. Build real-time data processing pipelines using platforms like Apache Kafka or cloud-native tools. Optimize batch processing workflows with tools like Apache Spark and Flink for scalable performance. Infrastructure Automation: Implement … Integrate cloud-based data services with data lakes and warehouses. Build and automate CI/CD pipelines with Jenkins, GitLab CI/CD, or Apache Airflow. Develop automated test suites for data pipelines, ensuring data quality and transformation integrity. Monitoring & Performance Optimization: Monitor data pipelines with tools like Prometheus More ❯

IaC), automation & configuration management Ansible (plus Puppet, Saltstack), Terraform, CloudFormation NodeJS, REACT/MaterialUI (plus Angular), Python, JavaScript Big data processing and analysis, e.g. Apache Hadoop (CDH), Apache Spark RedHat Enterprise Linux, CentOS, Debian or Ubuntu Java 8, Spring framework (preferably Spring boot), AMQP - RabbitMQ Open source More ❯

IaC), automation & configuration management; • Ansible (plus Puppet, Saltstack), Terraform, CloudFormation; • NodeJS, REACT/MaterialUI (plus Angular), Python, JavaScript; • Big data processing and analysis, e.g. Apache Hadoop (CDH), Apache Spark; • RedHat Enterprise Linux, CentOS, Debian or Ubuntu. • Java 8, Spring framework (preferably Spring boot), AMQP - RabbitMQ, • Open source More ❯

to Have: AWS Certified Data Engineer, or AWS Certified Data Analytics, or AWS Certified Solutions Architect Experience with big data tools and technologies like Apache Spark, Hadoop, and Kafka Knowledge of CI/CD pipelines and automation tools such as Jenkins or GitLab CI About Adastra For more More ❯

platform management roles, with 5+ years in leadership positions. Expertise in modern data platforms (e.g., Azure, AWS, Google Cloud) and big data technologies (e.g., Spark, Kafka, Hadoop). Strong knowledge of data governance frameworks, regulatory compliance (e.g., GDPR, CCPA), and data security best practices. Proven experience in enterprise-level More ❯

Qualifications: Master's or Ph.D. degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related fields. Proven experience in Databricks and its ecosystem (Spark, Delta Lake, MLflow, etc.). Strong proficiency in Python and R for data analysis, machine learning, and data visualization. In-depth knowledge of cloud … BigQuery, Redshift, Data Lakes). Expertise in SQL for querying large datasets and optimizing performance. Experience working with big data technologies such as Hadoop, Apache Spark, and other distributed computing frameworks. Solid understanding of machine learning algorithms, data preprocessing, model tuning, and evaluation. Experience in working with LLM More ❯

Terraform, Flask, Pandas, FastAPI, Dagster, GraphQL, SQLAlchemy, GitLab, Athena. Your Trusted Companions : Docker, Snowflake, MongoDB, Relational Databases (eg MySQL, PostgreSQL), Dagster, Airflow/Luigi, Spark, Kubernetes. Your AWS Kingdom : Lambda, Redshift, EC2, ELB, IAM, RDS, Route53, S3-the building blocks of cloud mastery. Your Philosophy : Continuous integration/deployments More ❯

Intelligence platform, either on Azure or AWS. Good working knowledge of Databricks components: DeltaLake, Unity Catalog, ML Flow, etc. Expertise in SQL, Python and Spark (Scala or Python). Experience working with relational SQL databases either on premises or in the cloud. Experience delivering multiple solutions using key techniques More ❯

and BI solutions. Ensure data accuracy, integrity, and consistency across the data platform. Knowledge, Skills and Experience: Essentia l Strong expertise in Databricks and Apache Spark for data engineering and analytics. Proficient in SQL and Python/PySpark for data transformation and analysis. Experience in data lakehouse development More ❯

Data Engineer (Python Spark SQL) *Newcastle Onsite* to £70k Do you have a first class education combined with Data Engineering skills? You could be progressing your career at a start-up Investment Management firm that have secure backing, an established Hedge Fund client as a partner and massive growth … scientific discipline, backed by minimum A A B grades at A-level You have commercial Data Engineering experience working with technologies such as SQL, Apache Spark and Python including PySpark and Pandas You have a good understanding of modern data engineering best practices Ideally you will also have … will earn a competitive salary (to £70k) plus significant bonus and benefits package. Apply now to find out more about this Data Engineer (Python Spark SQL) opportunity. At Client Server we believe in a diverse workplace that allows people to play to their strengths and continually learn. We're More ❯

independently Experience in working with data visualization tools Experience in GCP tools – Cloud Function, Dataflow, Dataproc and Bigquery Experience in data processing framework – Beam, Spark, Hive, Flink GCP data engineering certification is a merit Have hands on experience in Analytical tools such as powerBI or similar visualization tools Exhibit More ❯

ll Bring 5+ years in data/analytics engineering, including 2+ years in a leadership or mentoring role. Strong hands-on expertise in Databricks , Spark , Python , PySpark , and Delta Live Tables . Experience designing and delivering scalable data pipelines and streaming data processing (e.g., Kafka , AWS Kinesis , or Azure More ❯

knowledge of programming languages, specifically Python and SQL. Expertise in data management, data architecture, and data visualization techniques. Experience with data processing frameworks like Apache Spark, Hadoop, or Flink. Strong understanding of database systems (SQL and NoSQL) and data warehousing technologies. Familiarity with cloud computing platforms (AWS, Azure More ❯

Glue, Athena, Redshift, Kinesis, Step Functions, and Lake Formation. Strong programming skills in Python and PySpark for data processing and automation. Extensive SQL experience (Spark-SQL, MySQL, Presto SQL) and familiarity with NoSQL databases (DynamoDB, MongoDB, etc.). Proficiency in Infrastructure-as-Code (Terraform, CloudFormation) for automating AWS data More ❯

issues . Ability to work in a fast-paced, high-growth environment with a product-oriented mindset . Bonus: Experience with big data tools (Spark, Kafka) and feature stores . Why Join Us? Work on cutting-edge AI and ML infrastructure supporting generative AI products. Be part of a More ❯

error handling, code optimization). Proficiency in SQL – comfortable designing databases, writing complex queries, and handling performance tuning. Experience with Databricks (or a comparable Spark environment) – ability to build data pipelines, schedule jobs, and create dashboards/notebooks. Experience with Azure services (Data Factory, Synapse, or similar) and knowledge More ❯

in commodities markets or broader financial markets. Knowledge of quantitative modeling, risk management, or algorithmic trading. Familiarity with big data technologies like Kafka, Hadoop, Spark, or similar. Why Work With Us? Impactful Work: Directly influence the profitability of the business by building technology that drives trading decisions. Innovative Culture More ❯

processes in the engineering delivery cycle including Agile and DevOps, Git, APIs, Containers, Microservices and Data Pipelines. Experience working with one or more of Spark, Kafka, or Snowflake My client have very limited interview slots and they are looking to fill this vacancy within the next 2 weeks. I More ❯

Argo, Dagster or similar. Skilled with data ingestion tools like Airbyte, Fivetran, etc. for diverse data sources. Expert in large-scale data processing with Spark or Dask. Strong in Python, Scala, C# or Java, cloud SDKs and APIs. AI/ML expertise for pipeline efficiency, familiar with TensorFlow, PyTorch More ❯

strong grasp of modern cloud architectures.?Expertise in data pipelines, ETL/ELT, and working with structured & unstructured data.?Strong skills in SQL, Python, Spark, or other relevant technologies.?Prior exposure to Microsoft Fabric is a huge plus -- but if you're eager to learn, we'll get you … repositories. 7. Document data architecture, processes, and workflows for reference and knowledge sharing. 8. Utilise programming languages (e.g., C#, Python, SQL) and technologies (e.g., Apache Spark, SSIS, .NET) to manipulate and analyse data. 9. Participate in code reviews, version control (e.g., using Git), and other software development best More ❯