1 to 25 of 76 Apache Spark Jobs in London

privacy, and security, ensuring our AI systems are developed and used responsibly and ethically. Tooling the Future: Get hands-on with cutting-edge technologies like Hugging Face, PyTorch, TensorFlow, Apache Spark, Apache Airflow, and other modern data and ML frameworks. Collaborate and Lead: Partner closely with ML Engineers, Data Scientists, and Researchers to understand their data needs … their data, compute, and storage services. Programming Prowess: Strong programming skills in Python and SQL are essential. Big Data Ecosystem Expertise: Hands-on experience with big data technologies like Apache Spark, Kafka, and data orchestration tools such as Apache Airflow or Prefect. ML Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong proficiency in SQL, including advanced query development and performance tuning. Good understanding of distributed computing principles and … automation pipelines. Experience working with relational databases such as PostgreSQL, MySQL, or equivalent platforms. Skilled in using containerization technologies including Docker and Kubernetes. Experience with workflow orchestration tools like Apache Airflow or Dagster. Familiar with streaming data pipelines and real-time analytics solutions. More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong proficiency in SQL, including advanced query development and performance tuning. Good understanding of distributed computing principles and … automation pipelines. Experience working with relational databases such as PostgreSQL, MySQL, or equivalent platforms. Skilled in using containerization technologies including Docker and Kubernetes. Experience with workflow orchestration tools like Apache Airflow or Dagster. Familiar with streaming data pipelines and real-time analytics solutions. More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong proficiency in SQL, including advanced query development and performance tuning. Good understanding of distributed computing principles and … automation pipelines. Experience working with relational databases such as PostgreSQL, MySQL, or equivalent platforms. Skilled in using containerization technologies including Docker and Kubernetes. Experience with workflow orchestration tools like Apache Airflow or Dagster. Familiar with streaming data pipelines and real-time analytics solutions. More ❯

Technical Expertise: Solid experience in Python programming, particularly using data manipulation and processing libraries such as Pandas, NumPy, and Apache Spark. Hands-on experience with open-source data frameworks like Apache Spark, Apache Kafka, and Apache Airflow. Strong proficiency in SQL, including advanced query development and performance tuning. Good understanding of distributed computing principles and … automation pipelines. Experience working with relational databases such as PostgreSQL, MySQL, or equivalent platforms. Skilled in using containerization technologies including Docker and Kubernetes. Experience with workflow orchestration tools like Apache Airflow or Dagster. Familiar with streaming data pipelines and real-time analytics solutions. More ❯

Be Doing You'll be a key contributor to the development of a next-generation data platform, with responsibilities including: Designing and implementing scalable data pipelines using Python and Apache Spark Building and orchestrating workflows using AWS services such as Glue , Lambda , S3 , and EMR Serverless Applying best practices in software engineering: CI/CD , version control , automated … testing , and modular design Supporting the development of a lakehouse architecture using Apache Iceberg Collaborating with product and business teams to deliver data-driven solutions Embedding observability and quality checks into data workflows Participating in code reviews, pair programming, and architectural discussions Gaining domain knowledge in financial data and sharing insights with the team What They're Looking For … for experience with type hints, linters, and testing frameworks like pytest) Solid understanding of data engineering fundamentals: ETL/ELT, schema evolution, batch processing Experience or strong interest in Apache Spark for distributed data processing Familiarity with AWS data tools (e.g., S3, Glue, Lambda, EMR) Strong communication skills and a collaborative mindset Comfortable working in Agile environments and More ❯

contract assignment. Key Requirements: Proven background in AI and data development Strong proficiency in Python , including data-focused libraries such as Pandas, NumPy, and PySpark Hands-on experience with Apache Spark (PySpark preferred) Solid understanding of data management and processing pipelines Experience in algorithm development and graph data structures is advantageous Active SC Clearance is mandatory Role Overview … You will play a key role in developing and delivering advanced AI solutions for a Government client . Responsibilities include: Designing, building, and maintaining data processing pipelines using Apache Spark Implementing ETL/ELT workflows for large-scale data sets Developing and optimising Python-based data ingestion tools Collaborating on the design and deployment of machine learning models … performance across distributed systems Contributing to data architecture and storage strategy design Working with cloud data platforms (AWS, Azure, or GCP) to deploy scalable solutions Monitoring, troubleshooting, and tuning Spark jobs for performance and cost efficiency Engaging regularly with customers and internal stakeholders This is an excellent opportunity to join a high-profile organisation on a long-term contract More ❯

contract assignment. Key Requirements: Proven background in AI and data development Strong proficiency in Python , including data-focused libraries such as Pandas, NumPy, and PySpark Hands-on experience with Apache Spark (PySpark preferred) Solid understanding of data management and processing pipelines Experience in algorithm development and graph data structures is advantageous Active SC Clearance is mandatory Role Overview … You will play a key role in developing and delivering advanced AI solutions for a Government client . Responsibilities include: Designing, building, and maintaining data processing pipelines using Apache Spark Implementing ETL/ELT workflows for large-scale data sets Developing and optimising Python-based data ingestion tools Collaborating on the design and deployment of machine learning models … performance across distributed systems Contributing to data architecture and storage strategy design Working with cloud data platforms (AWS, Azure, or GCP) to deploy scalable solutions Monitoring, troubleshooting, and tuning Spark jobs for performance and cost efficiency Engaging regularly with customers and internal stakeholders This is an excellent opportunity to join a high-profile organisation on a long-term contract More ❯

design principles and methodologies Advanced knowledge of optimisation techniques for large-scale data processing Strong proficiency in SQL and Python for handling complex data problems Hands-on experience with Apache Spark (PySpark or Spark SQL) Experience with the Azure data stack Knowledge of workflow orchestration tools like Azure Data Factory or Apache Airflow Experience with containerisation … platforms Experience with data quality frameworks and implementation Understanding of data lineage and metadata management Experience with technical project management Experience with data visualisation tools like Power BI or Apache Superset Experience with other cloud data platforms like AWS, GCP or Oracle Experience with modern unified data platforms like Databricks or Microsoft Fabric Experience with Kubernetes for container orchestration … Understanding of streaming technologies (Apache Kafka, event-based architectures) Software engineering background with SOLID principles understanding Experience with high-performance, large-scale data systems Knowledge of recent innovations in AI/ML and GenAI Defence/Public Sector consultant experience Security Clearance: UKSV (United Kingdom Security Vetting) clearance is required for this role, with Security Check (SC) as the More ❯

and solution design. Drive excellence in data governance, cloud security, and continuous improvement . What You Bring Solid track record of designing and scaling modern data architectures. Mastery of Apache Spark , PySpark , and Databricks (Delta Lake, Unity Catalog, MLflow, Workflows). Strong command of Python and SQL for building reusable, modular pipelines. Expertise in AWS (S3, Lambda, Glue More ❯

two of the following: Python, 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, testing frameworks, CI/CD More ❯

platform. Candidate Profile: Proven experience as a Data Engineer, with strong expertise in designing and managing large-scale data systems. Hands-on proficiency with modern data technologies such as Spark, Kafka, Airflow, or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. More ❯

formats (e.g., NOAA, ECMWF, GFS, satellite, radar, sensor networks). Beneficial Proficient in one or more OO programming languages (e.g., Java, C#). Experience with distributed computing frameworks (e.g., Spark, Dask, Slurm). Experience with event-driven, asynchronous architectures and messaging technologies (e.g., Kafka, RabbitMQ). Experience with cloud platforms (e.g., AWS, GCP, Azure). Experience with orchestration and More ❯

e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Ability to scope and effectively deliver projects What we offer Equity options - share in More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines More ❯

of data modelling and data warehousing concepts Familiarity with version control systems, particularly Git Desirable Skills: Experience with infrastructure as code tools such as Terraform or CloudFormation Exposure to Apache Spark for distributed data processing Familiarity with workflow orchestration tools such as Airflow or AWS Step Functions Understanding of containerisation using Docker Experience with CI/CD pipelines More ❯

Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid More ❯

Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid More ❯

Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid More ❯

Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid More ❯

observability. Preferred Qualifications Exposure to machine learning workflows, model lifecycle management, or data engineering platforms. Experience with distributed systems, event-driven architectures (e.g., Kafka), and big data platforms (e.g., Spark, Databricks). Familiarity with banking or financial domain use cases, including data governance and compliance-focused development. Knowledge of platform security, monitoring, and resilient architecture patterns. About us More ❯

experience with Trino/Starburst Enterprise/Galaxy administration/CLI. Implementation experience with container orchestration solutions (Kubernetes/OpenShift). Knowledge of Big Data (Hadoop/Hive/Spark) and Cloud technologies (AWS, Azure, GCP). Understanding of distributed system architecture, high availability, scalability, and fault tolerance. Familiarity with security authentication systems such as LDAP, Active Directory, OAuth2 More ❯

experience with Trino/Starburst Enterprise/Galaxy administration/CLI. Implementation experience with container orchestration solutions (Kubernetes/OpenShift). Knowledge of Big Data (Hadoop/Hive/Spark) and Cloud technologies (AWS, Azure, GCP). Understanding of distributed system architecture, high availability, scalability, and fault tolerance. Familiarity with security authentication systems such as LDAP, Active Directory, OAuth2 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 ❯

experience with AWS data platforms and related services. Solid grasp of data governance principles, including data quality, metadata management, and access control. Familiarity with big data technologies such as Spark and Hadoop, and distributed computing concepts. Proficiency in SQL and at least one programming language (e.g., Python, Java). Preferred Qualifications: Relevant certifications in data architecture, cloud platforms, or More ❯