1 to 25 of 64 Apache Spark Jobs in London

Document stores).Hands-on experience building, scaling, and shipping large-scale data platforms in production.Deep practical experience with distributed data processing frameworks (e.g., Apache Spark, Flink, Hadoop).Strong expertise in message brokers and event streaming platforms (e.g., Apache Kafka, Kinesis).End-to-end exposure to data pipeline … lifecycle development, including extensive experience with workflow orchestration tools (e.g., Apache Airflow, Dagster).Hands-on expertise with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lake architectures (e.g., Databricks, Delta Lake, Apache Iceberg).Advanced SQL skills and proficiency in Python. Strong background in modern software development practices ...

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 ...

strategic planningRequired Skills & ExperienceTechnical SkillsStrong proficiency in SQL and data modellingExcellent programming skills in Python, Scala, or JavaHands-on experience with distributed data frameworks (Spark, Hadoop)Experience with data pipelines and ETL toolsExpertise in at least one cloud platform:Azure (Synapse, Data Factory, Databricks)AWS (S3, Glue, Redshift, Lambda ...

continuous learning to understand new data management systems Strong proficiency in hands-on development using industry-standard tools and languages (e.g., SQL, Python, Spark, cloud platforms), with a commitment to code quality and delivery excellence Preferred qualifications, capabilities, and skills Hands-on experience with Databricks for scalable data engineering … analytics, and collaborative development, as well as proficiency in managing large datasets using Apache Iceberg for efficient, reliable table management and data lake optimization Experience architecting and implementing enterprise-scale data warehouses on cloud platforms (e.g., AWS, Azure, GCP), including migration from legacy systems Advanced proficiency in designing ...

engineers should be adept at Extract, Transform, Load (ETL) processes. This includes using frameworks such as the Medallion Architecture, as well as tools like Apache Airflow, Fivetran, Azure Data Factory, and Amazon Glue to automate data workflows and ensure data quality. Familiarity with cloud computing services, such … Cloud Platform, is increasingly important. Data engineers often leverage these platforms for scalable data storage and processing capabilities. Knowledge of big data frameworks like Apache Spark, Beam is crucial for handling large datasets and real-time data processing. Understanding data modelling techniques helps data engineers design efficient data ...

practitioner, you will collaborate with architects, engineers, and analysts to deliver secure, scalable, and high-performing migration solutions, leveraging technologies such as AWS Glue, Apache Iceberg, Python/PySpark, SQL, and YAML-based configurations.You will thrive in a collaborative, client-facing environment, with a passion for solving complex data … target cloud architecturesData Pipeline Testing & Validation (Core Focus)Test end-to-end ETL data solutions running on AWS services, including AWS Glue and Apache IcebergValidate data feed pipeline migrations transitioning to new AWS Data Lakehouse architecturesTest pipelines underpinned by:AI ETL acceleratorsPython/PySpark transformationsSQL-based logicYAML configuration-driven ...

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 Reporting ...

/ELT processes and data pipeline development Experience working with cloud platforms such as AWS, Azure or GCP Knowledge of technologies such as Spark, Kafka, Airflow or similar Experience with databases, data modelling and data warehouse solutions Understanding of CI/CD, software engineering best practices and secure development ...

quality and consistency across platforms while complying with governance policies. What You Bring: Core Development Skills: - Proficient in Python and SQL, with experience in Apache Spark. - Strong experience building backend services and APIs. Database Expertise: - Solid understanding of relational databases (SQL Server, PostgreSQL) and distributed NoSQL databases (Cassandra, MongoDB ...

Azure) Experience with: o Data warehousing and lake architectures o ETL/ELT pipeline development o SQL and NoSQL databases o Distributed computing frameworks (Spark, Kinesis etc) o Software development best practices including CI/CD, TDD and version control. o Containerisation tools like Docker or Kubernetes o Experience ...

maintain scalable Databricks pipelines (ETL, streaming, ML workflows).• Perform cluster and job performance tuning: optimize cluster sizing, caching, partitioning, and shuffle management.• Monitor Spark job metrics, analyze logs, and identify bottlenecks in data throughput or latency.• Implement cost-optimization strategies for Databricks jobs and clusters using autoscaling … using Databricks REST APIs, Prometheus, or Azure Monitor.• Maintain best practices for data engineering performance, testing, and documentation.Technical Skills Required• Strong proficiency with Databricks, Apache Spark (SQL, PySpark, Scala), and Delta Lake.• Deep understanding of Spark execution plans, shuffle optimization, and data partitioning strategies.• Experience tuning ...

with the Lead Data Engineer and partnering with data science, analytics and product teams. Key responsibilities * Build and maintain scalable data pipelines using Databricks, Apache Spark and Delta Lake * Develop and optimise batch and streaming workflows for reliability and performance * Contribute to lakehouse architecture and medallion pattern implementation … optimisation opportunities * Translate business requirements into technical solutions * Contribute to documentation and continuous improvement Required experience * Strong experience delivering production grade Databricks pipelines * Strong Spark, Delta Lake and Databricks Workflows experience * Python and SQL proficiency * Experience on Azure data platforms such as Azure Data Factory, ADLS Gen2, Azure DevOps ...

design approaches.You understand where traditional patterns remain appropriate – and where modern approaches add measurable value.Data Engineering & Platform Understanding:Strong knowledge of distributed processing (e.g. Apache Spark).Familiarity with Hadoop ecosystem components.Working knowledge of SQL and NoSQL technologies.Understanding of ETL/ELT design trade-offs.Awareness of DevOps practices ...

messaging architectures. Data Platforms & Cloud Technologies Hands-on experience with: Azure Data Lake Databricks Snowflake Delta Lake Azure Synapse Analytics/Microsoft Fabric Spark/PySpark Strong understanding of: Data Lake and Lakehouse architecture Hybrid cloud environments Enterprise integration patterns Modern data formats including Parquet, Avro, and ORC DevOps ...

engineering and promote their adoption.Drive continuous improvement in data infrastructure and tooling, leveraging cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark,dbt).Collaborate with PMs to manage project timelines, resource allocation, and deliverables to meet business goals.Work with data governance and compliance teams to ensure … expertise in data pipeline development, ETL/ELT processes, and data warehousing solutions.Proficient with cloud platforms (AWS, GCP, Azure) and big data tools like Apache Spark, Python, etc.Experience with relational and NoSQL databases.Solid understanding of data modeling, data architecture, engineering frameworksProven ability to lead and scale engineering teams ...

optimising ETL/ELT pipelines. Strong understanding of Lakehouse, Data Warehouse, and Data Lake architectures. Experience with Azure Data Factory, Azure Synapse, and Apache Spark. Knowledge of data modelling, semantic models, and enterprise reporting solutions. Experience implementing data governance, security, and quality frameworks. Strong understanding of modern data engineering ...

progression taking customers from EDW to the full capabilities of the Data Intelligence Platform.Demonstrated competence in the Lakehouse architecture including hands-on experience with Apache Spark, Python and SQLExcellent communication skills; both written and verbalPublic Cloud Architecting: Hands-on experience designing and implementing big data architectures within major ...

PostgreSQL (or similar relational databases) and NoSQL databases. Experience with vector databases such as Qdrant, Milvus or pgvector . Familiarity with technologies such as Apache Spark, Airflow, Kafka, Elasticsearch/OpenSearch, Pandas and Polars . Strong understanding of data modelling, storage architecture and performance optimisation. Desirable Experience working ...

stakeholders, and business leaders.Strong presentation, demo, and storytelling skills, with the ability to explain complex technical concepts clearly and credibly.Familiarity with SQL, Python, R, Apache Spark, or similar technologies is a plus.Experience with Alteryx or similar analytics platforms is highly desirable.Ability to work independently in a fast-paced ...

translate analytical needs into scalable Databricks-based solutions.Your expertiseYou have:• proven experience with Azure and Databricks in large-scale data environments• strong understanding of Spark, Hadoop ecosystems and big data engineering concepts• hands-on data engineering experience• experience delivering at least one end-to-end Databricks project• strong knowledge ...

security controls (RBAC, encryption, auditing, lineage). Essential Requirements Significant Databricks experience required, including production-scale deployments and optimisation. Strong hands-on capability with Spark/SQL, Delta Lake, orchestration, and data engineering patterns. Prior experience within a consulting practice with exposure to both pre-sales and delivery leading ...

systems Comfortable building from scratch in a fast-moving, product-led environment Experience with vector databases and vector search in modern AI systems Desirable: Spark, Airflow, Kafka, Elasticsearch/OpenSearch, event-driven architectures Cloud experience (AWS, GCP or Azure), GCP is a plus Why join High impact and ownership ...

security controls. Monitor, maintain and optimise data platforms to ensure performance and reliability. Skills and Experience Required: ETL development using Python or similar languages Apache Spark, NiFi, or Kafka Relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra) databases AWS and cloud-based data services Palantir Foundry Stakeholder Engagement ...

preparation. Machine learning and statistical methods, including model validation. Data analytics and visualisation techniques. Processing large datasets using batch or streaming tools such as Apache Spark. Data acquisition and fusion approaches. Cloud platforms (ideally AWS) and cloud-based data science solutions. DataOps principles and practices. Structured and unstructured databases. ...

Generative AI and Agentic AI, applied within enterprise environments.Experience with energy system modelling, grid analytics, demand forecasting or energy market data.Familiarity with distributed computing, Spark, PySpark or cloud-native data platforms.Experience developing models for planning, scenario analysis, operational decision support, model governance or regulatory reporting.Why Join CapcoDeliver high-impact ...