4 of 4 Permanent Apache Spark Jobs in Hampshire

of our clients data platform. This role is ideal for someone who thrives on building scalable data solutions and is confident working with modern tools such as Azure Databricks , Apache Kafka , and Spark . In this role, you'll play a key part in designing, delivering, and optimising data pipelines and architectures. Your focus will be on enabling … and want to make a meaningful impact in a collaborative, fast-paced environment, we want to hear from you !! Role and Responsibilities Designing and building scalable data pipelines using Apache Spark in Azure Databricks Developing real-time and batch data ingestion workflows, ideally using Apache Kafka Collaborating with data scientists, analysts, and business stakeholders to build high … and Experience We're seeking candidates who bring strong technical skills and a hands-on approach to modern data engineering. You should have: Proven experience with Azure Databricks and Apache Spark Working knowledge of Apache Kafka and real-time data streaming Strong proficiency in SQL and Python Familiarity with Azure Data Services and CI/CD pipelines More ❯

/Starburst Enterprise/Galaxy administration and CLI operations Container Orchestration : Proven track record with Kubernetes/OpenShift in production environments Big Data Ecosystem : Strong background in Hadoop, Hive, Spark, and cloud platforms (AWS/Azure/GCP) Systems Architecture : Understanding of distributed systems, high availability, and fault-tolerant design Security Protocols : Experience with LDAP, Active Directory, OAuth2, and More ❯

architecture, integration, governance frameworks, and privacy-enhancing technologies Experience with databases (SQL & NoSQL - Oracle, PostgreSQL, MongoDB), data warehousing, and ETL/ELT tools Familiarity with big data technologies (Hadoop, Spark, Kafka), cloud platforms (AWS, Azure, GCP), and API integrations Desirable: Data certifications (TOGAF, DAMA), government/foundational data experience, cloud-native platforms knowledge, AI/ML data requirements understanding More ❯

modern data platforms (Databricks, Snowflake, Kafka), container orchestration (Kubernetes/OpenShift), and multi-cloud deployments across AWS, Azure, GCP Advanced knowledge of Big Data ecosystems (Hadoop/Hive/Spark), data lakehouse architectures, mesh topologies, and real-time streaming platforms Strong Unix/Linux skills, database connectivity (JDBC/ODBC), authentication systems (LDAP, Active Directory, OAuth2), and data integration More ❯