1 to 25 of 65 Apache Spark Jobs in Central London

and contribute to technical roadmap planning Technical Skills: Great SQL skills with experience in complex query optimization Strong Python programming skills with experience in data processing libraries (pandas, NumPy, Apache Spark) Hands-on experience building and maintaining data ingestion pipelines Proven track record of optimising queries, code, and system performance Experience with open-source data processing frameworks (Apache Spark, Apache Kafka, Apache Airflow) Knowledge of distributed computing concepts and big data technologies Experience with version control systems (Git) and CI/CD practices Experience with relational databases (PostgreSQL, MySQL or similar) Experience with containerization technologies (Docker, Kubernetes) Experience with data orchestration tools (Apache Airflow or Dagster) Understanding of data warehousing concepts and dimensional More ❯

and contribute to technical roadmap planning Technical Skills: Great SQL skills with experience in complex query optimization Strong Python programming skills with experience in data processing libraries (pandas, NumPy, Apache Spark) Hands-on experience building and maintaining data ingestion pipelines Proven track record of optimising queries, code, and system performance Experience with open-source data processing frameworks (Apache Spark, Apache Kafka, Apache Airflow) Knowledge of distributed computing concepts and big data technologies Experience with version control systems (Git) and CI/CD practices Experience with relational databases (PostgreSQL, MySQL or similar) Experience with containerization technologies (Docker, Kubernetes) Experience with data orchestration tools (Apache Airflow or Dagster) Understanding of data warehousing concepts and dimensional More ❯

us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Your Role We are looking for a skilled Spark/Scala Developer to join our data engineering team. The ideal candidate will have hands-on experience in designing, developing, and maintaining large-scale data processing pipelines using Apache Spark and Scala. You will work closely with data scientists, analysts, and engineers to build efficient data solutions and enable data-driven decision-making. Key Responsibilities: Develop, optimize, and maintain data pipelines and ETL processes using Apache Spark and Scala. Design scalable and robust data processing solutions for batch and real-time data. Collaborate with cross … functional teams to gather requirements and translate them into technical specifications. Perform data ingestion, transformation, and cleansing from various structured and unstructured sources. Monitor and troubleshoot Spark jobs, ensuring high performance and reliability. Write clean, maintainable, and well-documented code. Participate in code reviews, design discussions, and agile ceremonies. Implement data quality and governance best practices. Stay updated with More ❯

us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Your Role We are looking for a skilled Spark/Scala Developer to join our data engineering team. The ideal candidate will have hands-on experience in designing, developing, and maintaining large-scale data processing pipelines using Apache Spark and Scala. You will work closely with data scientists, analysts, and engineers to build efficient data solutions and enable data-driven decision-making. Key Responsibilities: Develop, optimize, and maintain data pipelines and ETL processes using Apache Spark and Scala. Design scalable and robust data processing solutions for batch and real-time data. Collaborate with cross … functional teams to gather requirements and translate them into technical specifications. Perform data ingestion, transformation, and cleansing from various structured and unstructured sources. Monitor and troubleshoot Spark jobs, ensuring high performance and reliability. Write clean, maintainable, and well-documented code. Participate in code reviews, design discussions, and agile ceremonies. Implement data quality and governance best practices. Stay updated with More ❯

/MS in Computer Science, Software Engineering, or equivalent technical discipline. 8+ years of hands-on experience building large-scale distributed data pipelines and architectures. Expert-level knowledge in Apache Spark, PySpark, and Databricks—including experience with Delta Lake, Unity Catalog, MLflow, and Databricks Workflows. Deep proficiency in Python and SQL, with proven experience building modular, testable, reusable More ❯

/MS in Computer Science, Software Engineering, or equivalent technical discipline. 8+ years of hands-on experience building large-scale distributed data pipelines and architectures. Expert-level knowledge in Apache Spark, PySpark, and Databricks—including experience with Delta Lake, Unity Catalog, MLflow, and Databricks Workflows. Deep proficiency in Python and SQL, with proven experience building modular, testable, reusable More ❯

skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if you're More ❯

Skills Strong experience with Azure data services (Data Factory, Synapse, Blob Storage, etc.). Proficiency in SQL for data manipulation, transformation, and performance optimisation. Hands-on experience with Databricks (Spark, Delta Lake, notebooks). Solid understanding of data architecture principles and cloud-native design. Experience working in consultancy or client-facing roles is highly desirable. Familiarity with CI/ More ❯

Skills Strong experience with Azure data services (Data Factory, Synapse, Blob Storage, etc.). Proficiency in SQL for data manipulation, transformation, and performance optimisation. Hands-on experience with Databricks (Spark, Delta Lake, notebooks). Solid understanding of data architecture principles and cloud-native design. Experience working in consultancy or client-facing roles is highly desirable. Familiarity with CI/ 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 ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

Science, Computer Science, or a related field. 5+ years of experience in data engineering and data quality. Strong proficiency in Python/Java, SQL, and data processing frameworks including Apache Spark. Knowledge of machine learning and its data requirements. Attention to detail and a strong commitment to data integrity. Excellent problem-solving skills and ability to work in a More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD … experience: Experience with efficient, reliable data pipelines that improve time-to-insight. Knowledge of secure, auditable, and compliant data workflows. Know how on optimising performance and reducing costs through Spark and Databricks tuning. Be able to create reusable, well-documented tools enabling collaboration across teams. A culture of engineering excellence driven by mentoring and high-quality practices. Preferred Experience … Databricks in a SaaS environment, Spark, Python, and database technologies. Event-driven and distributed systems (Kafka, AWS SNS/SQS, Java, Python). Data Governance, Data Lakehouse/Data Intelligence platforms. AI software delivery and AI data preparation. More ❯

scalable pipelines, data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD … experience: Experience with efficient, reliable data pipelines that improve time-to-insight. Knowledge of secure, auditable, and compliant data workflows. Know how on optimising performance and reducing costs through Spark and Databricks tuning. Be able to create reusable, well-documented tools enabling collaboration across teams. A culture of engineering excellence driven by mentoring and high-quality practices. Preferred Experience … Databricks in a SaaS environment, Spark, Python, and database technologies. Event-driven and distributed systems (Kafka, AWS SNS/SQS, Java, Python). Data Governance, Data Lakehouse/Data Intelligence platforms. AI software delivery and AI data preparation. More ❯

data modelling techniques + data integration patterns. Experience of working with complex data pipelines, large data sets, data pipeline optimization + data architecture design. Implementing complex data transformations using Spark, PySpark or Scala + working with SQL/MySQL databases. Experience with data quality, data governance processes, Git version control + Agile development environments. Azure Data Engineer certification preferred More ❯

GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with DevOps principles, containerisation and CI/CD tools such as Jenkins or GitHub More ❯

data reliability, scalability, and performance across the platform 🧩 The Tech Environment You’ll likely be working with some combination of: Languages: Python, Scala, Go Streaming: Kafka/Flink/Spark Structured Streaming Workflow orchestration: Airflow/Prefect/Dagster Data storage & processing: Snowflake/Detabricks/BigQuery/Redshift Infrastructure: Docker/Kubernetes/Terraform/dbt Monitoring: Prometheus More ❯

teams to build scalable data pipelines and contribute to digital transformation initiatives across government departments. Key Responsibilities Design, develop and maintain robust data pipelines using PostgreSQL and Airflow or Apache Spark Collaborate with frontend/backend developers using Node.js or React Implement best practices in data modelling, ETL processes and performance optimisation Contribute to containerised deployments (Docker/… within Agile teams and support DevOps practices What We're Looking For Proven experience as a Data Engineer in complex environments Strong proficiency in PostgreSQL and either Airflow or Spark Solid understanding of Node.js or React for integration and tooling Familiarity with containerisation technologies (Docker/Kubernetes) is a plus Excellent communication and stakeholder engagement skills Experience working within More ❯

a focus on having delivered in Microsoft Azure Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure Data Engineering certifications Databricks certifications What's in it for you: 📍Location: London More ❯

a focus on having delivered in Microsoft Azure Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure Data Engineering certifications Databricks certifications What's in it for you: 📍Location: London More ❯

engineering with a strong focus on building scalable data pipelines Expertise in Azure Databricks (7+years) including building and managing ETL pipelines using PySpark or Scala (essential) Solid understanding of Apache Spark, Delta Lake, and distributed data processing concepts Hands-on experience with Azure Data Lake Storage Gen2, Azure Data Factory, and Azure Synapse Analytics Proficiency in SQL and More ❯

testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to detail. More ❯

testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus. 5. Familiarity with scripting languages like python, java, or shell scripting. 6. Excellent analytical and problem-solving skills with a keen attention to detail. More ❯

Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure … Databricks Implementation: Work extensively with Azure Databricks Unity Catalog, including Delta Lake, Spark SQL, and other relevant services. Implement best practices for Databricks development and deployment. Optimise Databricks workloads for performance and cost. Need to program using the languages such as SQL, Python, R, YAML and JavaScript Data Integration: Integrate data from various sources, including relational databases, APIs, and … best practices. Essential Skills & Experience: 10+ years of experience in data engineering, with at least 3+ years of hands-on experience with Azure Databricks. Strong proficiency in Python and Spark (PySpark) or Scala. Deep understanding of data warehousing principles, data modelling techniques, and data integration patterns. Extensive experience with Azure data services, including Azure Data Factory, Azure Blob Storage More ❯

Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure … Databricks Implementation: Work extensively with Azure Databricks Unity Catalog, including Delta Lake, Spark SQL, and other relevant services. Implement best practices for Databricks development and deployment. Optimise Databricks workloads for performance and cost. Need to program using the languages such as SQL, Python, R, YAML and JavaScript Data Integration: Integrate data from various sources, including relational databases, APIs, and … best practices. Essential Skills & Experience: 10+ years of experience in data engineering, with at least 3+ years of hands-on experience with Azure Databricks. Strong proficiency in Python and Spark (PySpark) or Scala. Deep understanding of data warehousing principles, data modelling techniques, and data integration patterns. Extensive experience with Azure data services, including Azure Data Factory, Azure Blob Storage More ❯