76 to 100 of 1,304 Apache Spark Jobs in the UK

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 ❯

in data engineering roles with progressively increasing responsibility Proven experience designing and implementing complex data pipelines at scale Strong knowledge of distributed computing frameworks (Spark, Hadoop ecosystem) Experience with cloud-based data platforms (AWS, Azure, GCP) Proficiency in data orchestration tools (Airflow, Prefect, Dagster, or similar) Solid programming skills More ❯

with cloud data platforms such as GCP (BigQuery, Dataflow) or Azure (Data Factory, Synapse) Expert in SQL, MongoDB and distributed data systems such as Spark, Databricks or Kafka Familiarity with data warehousing concepts and tools (e.g. Snowflake) Experience with CI/CD pipelines, containerization (Docker), and infrastructure-as-code More ❯

with cloud data platforms such as GCP (BigQuery, Dataflow) or Azure (Data Factory, Synapse) Expert in SQL, MongoDB and distributed data systems such as Spark, Databricks or Kafka Familiarity with data warehousing concepts and tools (e.g. Snowflake) Experience with CI/CD pipelines, containerization (Docker), and infrastructure-as-code More ❯

similar role, with a focus on data infrastructure management Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure). Ideally some programming skills in languages like Python, Java, or Scala, with More ❯

with TensorFlow, PyTorch, Scikit-learn, etc. is a strong plus. You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS. You care about More ❯

applications through bug fixes and code refactoring. Leverage the latest data technologies and programming languages, including Python, Scala, and Java, along with systems like Spark, Kafka, and Airflow, within cloud services such as AWS. Ensure the ongoing maintenance, troubleshooting, optimization, and reliability of data systems, including timely resolution of … NoSQL databases (e.g., PostgreSQL, MongoDB) and data modeling principles. Proven ability to design, build, and maintain scalable data pipelines and workflows using tools like Apache Airflow or similar. Strong problem-solving and analytical skills. Excellent communication and collaboration skills. Nice to have: Hands-on experience with data warehouse and … lakehouse architectures (e.g., Databricks, Snowflake, or similar). Experience with big data frameworks (e.g., Apache Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, or GCP). More ❯

processes. Technical Skills Programming: Proficiency in Python, Java, Scala, or similar languages. Big Data Technologies: Hands-on experience with big data tools e.g. (Databricks, Apache Spark, Hadoop). Cloud Platforms: Familiarity with AWS, Azure, GCP, or other cloud ecosystems for data engineering tasks. Expertise in relational databases (e.g. … postgres, sql server) Data Integration Tools: Knowledge of platforms like Airflow, Apache NiFi, or Talend. Data Storage and Modelling: Experience with data warehousing tools (e.g. Snowflake, Redshift, BigQuery) and schema design. Version Control and CI/CD: Familiarity with Git, Docker, and CI/CD pipelines for deployment. Experience More ❯

and scaling data systems. Highly desired experience with Azure, particularly Lakehouse and Eventhouse architectures. Experience with relevant infrastructure and tools including NATS, Power BI, Apache Spark/Databricks, and PySpark. Hands-on experience with data warehousing methodologies and optimization libraries (e.g., OR-Tools). Experience with log analysis More ❯

most complex projects - individually or by leading small delivery teams. Our projects are fast-paced, typically 2 to 4 months long, and primarily use Apache Spark/Databricks on AWS/Azure. You will manage customer relationships either alone or with a Project Manager, and support our pre More ❯

or a related field, with a focus on building scalable data systems and platforms. Strong expertise with modern data tools and frameworks such as Spark , dbt , Airflow , Kafka , Databricks , and cloud-native services (AWS, GCP, or Azure). Deep understanding of data modeling , distributed systems , streaming architectures , and ETL More ❯

industries Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights Write code in SQL, Python, and Spark following software engineering best practices Collaborate with stakeholders and customers to ensure successful project delivery Who we are looking for We are looking for More ❯

SQL, Java Commercial experience in client-facing projects is a plus, especially within multi-disciplinary teams Deep knowledge of database technologies: Distributed systems (e.g., Spark, Hadoop, EMR) RDBMS (e.g., SQL Server, Oracle, PostgreSQL, MySQL) NoSQL (e.g., MongoDB, Cassandra, DynamoDB, Neo4j) Solid understanding of software engineering best practices - code reviews 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 ❯

data infrastructure and capabilities. What is needed to succeed: Technical skills: Problem-solving team player with an analytical mind. Strong knowledge of SQL and Spark SQL. Understanding of dimensional data modelling concepts. Experience with Azure Synapse Analytics. Understanding of streaming data ingestion processes. Ability to develop/manage Apache Spark data processing applications using PySpark on Databricks. Experience with version control (e.g., Git), DevOps, and CI/CD. Experience with Python. Experience with Microsoft data platform, Microsoft Azure stack, and Databricks. Experience in marketing is a plus. Soft Skills: Strong problem-solving skills and the ability to More ❯

architectures for ML frameworks in complex problem spaces in collaboration with product teams Experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS Where You'll Be We offer you the flexibility to work where More ❯

and the ability to oversee end-to-end solutions while leading projects are essential. Required Tools and Technologies: Microsoft Azure and cloud computing concepts Apache Spark – Databricks, Microsoft Fabric, or other Spark engines Python SQL – complex high-performance queries Azure Data Factory or other orchestration tools Azure More ❯

tech stack with the ability to see the end-to-end solution across multiple concurrent projects. Key Responsibilities: Microsoft Azure and cloud computing concepts Apache Spark – Databricks, Microsoft Fabric or another Spark engine Python – we build most of our solutions in Python SQL – writing complex high-performance More ❯

processes. Technical Skills Programming: Proficiency in Python, Java, Scala, or similar languages. Big Data Technologies: Hands-on experience with big data tools e.g. (Databricks, Apache Spark, Hadoop). Cloud Platforms: Familiarity with AWS, Azure, GCP, or other cloud ecosystems for data engineering tasks. Expertise in relational databases (e.g. … postgres, sql server) Data Integration Tools: Knowledge of platforms like Airflow, Apache NiFi, or Talend. Data Storage and Modelling: Experience with data warehousing tools (e.g. Snowflake, Redshift, BigQuery) and schema design. Version Control and CI/CD: Familiarity with Git, Docker, and CI/CD pipelines for deployment. Experience More ❯

Data Engineering product area. This next-generation cloud-native service empowers customers to run large-scale data engineering workflows—using industry-standard tools like Apache Spark and Apache Airflow—with just a few clicks, across both on-premises and public cloud environments. You'll play a critical … lead their own teams across multiple time zones Oversee a global team, many of whom are active contributors to open source communities like the Apache Software Foundation Own both technical direction and people management within the team Ensure consistent, high-quality software delivery through iterative releases Hire, manage, coach More ❯

years, and ability to obtain security clearance. Preferred Skills Experience with cloud platforms (IBM Cloud, AWS, Azure). Knowledge of big data frameworks (Apache Spark, Hadoop). Experience with data warehousing tools like IBM Cognos or Tableau. Certifications in relevant technologies are a plus. Additional Details Seniority level More ❯

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 More ❯

mixture of Enterprise and SME environments Proficiency in Python, SQL, Azure Data Factory, Azure Synapse Analytics, Azure Data Lakes, and big data technologies like Apache Spark Experience with DevOps practices and CI/CD pipelines in an Azure environment is a plus. Certification in Azure (e.g., Microsoft Certified More ❯

modelling (relational, NoSQL) and ETL/ELT processes. Experience with data integration tools (e.g., Kafka, Talend) and APIs. Familiarity with big data technologies (Hadoop, Spark) and real-time streaming. Expertise in cloud security, data governance, and compliance (GDPR, HIPAA). Strong SQL skills and proficiency in at least one More ❯

a team. Preferred Qualifications: Master's degree in Computer Science, Data Science, or a related field. Experience with big data technologies such as Hadoop, Spark, or Kafka. Experience with data visualization tools such as Power BI, Tableau, or Qlik. Certifications in Azure data and AI technologies. Benefits Salary: We More ❯