26 to 50 of 254 Apache Spark Jobs in London

delivery across a range of projects, including data analysis, extraction, transformation, and loading, data intelligence, data security and proven experience in their technologies (e.g. Spark, cloud-based ETL services, Python, Kafka, SQL, Airflow) You have experience in assessing the relevant data quality issues based on data sources & uses cases ...

Data Warehousing concepts. Enterprise ETL tools such as Informatica, Talend, Datastage or Alteryx. Project experience using the any of the following technologies: Hadoop, Spark, Scala, Oracle, Pega, Salesforce. Cross and multi-platform experience. Team building and leading. Qualifications You must be: Willing to work on client sites, potentially ...

operating ETL/ELT pipelines and large‐scale data architectures. Deep hands‐on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with similar technologies is essential). ...

operating ETL/ELT pipelines and large-scale data architectures. Hands-on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with similar technologies is essential). Ability ...

environments. Technical Skills: Experience building and operating ETL/ELT pipelines. Hands-on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with some of these or similar ...

operating ETL/ELT pipelines and large-scale data architectures. Deep hands‐on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with similar technologies is essential). ...

possess hands‐on experience with one or more of the following technological areas (or their equivalent cloud‐native alternatives): Analytics & Platform Frameworks like Apache Spark or similar cloud-specific services. Transformation & Orchestration tools Database Technologies Libraries & Schema Management Storage Formats: Familiarity managing diverse data types through formats like ...

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

comfortable operating across both clouds. Familiarity with OLAP and OLTP storage systems and an eagerness to build expertise in stream processing technologies such as Apache Flink, Kafka, or Spark. (Nice to have: ClickHouse.) Familiarity with observability tooling such as Grafana or Datadog, and a good instinct for keeping systems ...

experience with one or more cloud data ecosystems: Azure (Data Factory, Synapse, Fabric, ADLS, Databricks) AWS (Glue, Redshift, EMR) GCP (BigQuery, Dataflow) Databricks (Spark/PySpark) Snowflake (SQL, Snowpark, performance tuning) Strong SQL and/or Python capability, and familiarity with tools such as dbt, Git, CI/ ...

Data Engineer 6 Month Contract Location: London (Onsite 4 days a week) Rate: £700 - £800 per day (INSIDE IR35) Skills: Python, Azure, Kubernetes, Apache Airflow, Apache Spark, DV Clearance We are looking to recruit a DV Cleared Data Engineer for a leading technology consultancy click apply ...

value. Excellent analytical, problem-solving, and communication skills. Proven experience leading data modernisation initiatives across multiple sectors. Technical Expertise Proficiency with big data technologies: Apache Spark, Kafka, Confluent, Databricks, Unity Catalog. Strong knowledge of cloud ecosystems (AWS, Azure, GCP) and infrastructure-as-code (Terraform, CloudFormation). Hands ...

able to guide how one could deploy infrastructure into different environments. Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop. Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes) Ability to create ...

agreed scope, acting as the key point of escalation for decisions that impact your area of work - Demonstrable experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse ...

Security In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience Preferred qualifications, capabilities, and skills Advanced Apache Spark experience(PySpark/Spark SQL), including performance tuning (partitioning, shuffle optimization, caching), troubleshooting, and designing scalable batch/stream processing patterns. Deep ...

cleansed, conformed business layers) while securely handling identifiable data. Scalable Data Processing: Develop, tune, and monitor large-scale batch processing pipelines using Azure Databricks (Spark-based processing) and PySpark. Orchestration & Workflow: Build automated data workflows using Microsoft Fabric Data Factory and Azure Data Factory to move data efficiently across … Microsoft Azure, with practical exposure to the Microsoft Fabric ecosystem (OneLake, Data Factory, Fabric Lakehouse). Big Data Processing: Deep technical expertise with Apache Spark/Azure Databricks for distributed compute, memory optimization, and Delta Lake formats. Data Engineering Languages: Advanced proficiency in SQL (T-SQL, SparkSQL ...

with data warehousing concepts and technologies (e.g., Azure Synapse Analytics, Azure Data Lake Storage). Familiarity with big data technologies and frameworks (e.g., Hadoop, Spark) is a plus. Knowledge of data governance and data security best practices. Strong problem-solving skills and attention to detail. Excellent communication and collaboration ...

large-scale ETL development. Proficiency in SQL and programming languages such as Python, Java, or Scala. Hands‐on experience with big data frameworks (e.g., Spark, Hadoop, Flink) and cloud platforms (AWS, GCP, or Azure). Familiarity with data warehouse technologies (e.g., Snowflake, Redshift, BigQuery) and workflow orchestration tools (e.g. ...

Excellent Python and SQL Solid grasp of data modelling, warehousing and lakehouse concepts Hands-on with orchestration (e.g. Airflow, Dagster) and distributed processing (e.g. Spark) Experience with cloud data platforms (AWS, Azure or GCP) and containerised deployment (Docker, Kubernetes) Good engineering practice: version control, CI/CD, testing ...

maintain SC clearance. Desirable AWS certification at Associate or Professional level Experience with streaming and event-driven data technologies Experience with technologies such as Spark, Kafka or Databricks Experience delivering data platforms within public sector, defence or other regulated environments Experience working within secure environments and understanding associated security ...

methods (streaming vs batch) Familiarity with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.), cloud platforms (AWS, Azure, GCP) and engineering tools (Pandas, Spark, dbt, LangChain, etc.) Exposure to modern software development practices, including version control (Git) and foundational concepts in DevOps and MLOps/LLMOps ...

Company description Publicis Media harnesses the power of modern media through leading agency brands Dysrupt, Infinite Roar, Publicis Collective, Publicis Health Media, Spark Foundry, Starcom and Zenith, as well as global accelerator PMX; immersive experience group PMCI and access to integrated platform-based technologies and offerings from CJ, Epsilon … marketing platforms. Build and optimize schemas, transformations, and ETL logic for high‐performance, reusable data workflows. Contribute directly to the DFP codebase (Python, SQL, Spark) — developing pipelines and infrastructure alongside the engineering team. Establish data versioning, testing, and governance frameworks ensuring reliability, lineage, and compliance. Data Engineering Leadership Drive ...

with data integrations and efficient data transfers. Knowledge of data modeling, data warehousing concepts, and query optimization techniques. Experience with distributed data processing using Apache Spark. Experience with Airflow for workflow orchestration, scheduling, and monitoring data pipelines. Cloud expertise, particularly AWS, including services such as S3, Glue, Athena ...

Must-Have Skills & Experience Deep expertise designing and building scalable data pipelines and data products in cloud environments Strong hands-on experience with Databricks, Spark, SQL, and Python Experience developing and optimizing batch and real-time data processing solutions Strong understanding of modern data architecture patterns, including Kimball, Data ...

Must-Have Skills & Experience Deep expertise designing and building scalable data pipelines and data products in cloud environments Strong hands-on experience with Databricks, Spark, SQL, and Python Experience developing and optimizing batch and real-time data processing solutions Strong understanding of modern data architecture patterns, including Kimball, Data ...