51 to 75 of 317 Apache Spark Jobs in London

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 ...

working with or within the public sector Familiarity using AI tools to enhance the quality & pace of your output Technologies we love Languages: Python, Spark, SQL Tools: AWS, Azure, Git, Rest APIs, Kubernetes, Docker, Terraform, Datadog Datastores: Databricks, OpenSearch, Postgres Equal Opportunity Statement At Altana, we believe that ...

e.g., AWS, Azure, GCP) and their AI/ML services.Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL, data pipelines, and automated workflows for moving and processing data.Data Governance: Adherence to data governance, security, and privacy standards ...

Python, or similar languages relevant to data manipulation and scripting.Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL/ELT, data warehousing, and automated workflows for moving and processing data.Data Governance: Strong understanding and practical experience with ...

/CD, Application Resiliency, and SecurityIn-depth knowledge of the financial services industry and their IT systemsPractical cloud native experiencePreferred qualifications, capabilities, and skillsAdvanced Apache Spark experience (PySpark/Spark SQL), including performance tuning (partitioning, shuffle optimization, caching), troubleshooting, and designing scalable batch/stream processing patterns.Deep ...

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 ...

testing, and deployment.Deep understanding of Quantexa components such as:Entity Resolution (ER)Scoring FrameworkContextual Network GenerationUI ConfigurationStrong background in Big Data technologies, including:Scala, Apache Spark, Hadoop, ElasticSearchExperience with data modelling and design in the context of large-scale analytics platforms.Strong stakeholder management and communication skills – capable ...

deployment. Deep understanding of Quantexa components such as: Entity Resolution (ER)Scoring FrameworkContextual Network GenerationUI ConfigurationStrong background in Big Data technologies, including: Scala, Apache Spark, Hadoop, ElasticSearchExperience with data modelling and design in the context of large-scale analytics platforms. Strong stakeholder management and communication skills – capable ...

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 ...

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 ...

following: Python, SQL, JavaCommercial experience in client-facing projects is a plus, especially within multi-disciplinary teamsDeep 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 ...

.• Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon).• Familiarity with data lake architectures and distributed processing frameworks (e.g., Spark, Hadoop).• Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.• Understanding of data governance, security, and compliance frameworks.• Exposure ...

Have:Certifications: Google Cloud or AWS Certified Solutions Architect certification.ETL and Data Pipeline Expertise: Experience with ETL tools and Hadoop-based technologies (e.g., Spark) and/or batch/streaming data pipelines such as Beam and Flink.Data Architecture: Proven ability in designing and building data lake and data warehouse ...

Have: Certifications: Google Cloud or AWS Certified Solutions Architect certification. ETL and Data Pipeline Expertise: Experience with ETL tools and Hadoop-based technologies (e.g., Spark) and/or batch/streaming data pipelines such as Beam and Flink. Data Architecture: Proven ability in designing and building data lake ...

deliver agreed scope, acting as the key point of escalation for decisions that impact your area of workDemonstrable experience of building data pipelines using Spark, Python or SQLExperience working with AWS and its data and AI/ML services such as SageMakerExperience of big data and lakehouse platforms ...

Python, or similar languages relevant to data manipulation and scripting.Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL/ELT, data warehousing, and automated workflows for moving and processing data.Familiarity with data modelling techniques (e.g., dimensional, relational) and data ...

root-cause analysis. Experience building or supporting production data pipelines in a collaborative engineering environment. Experience working with distributed data processing frameworks such as Apache Spark. Working knowledge of common data formats such as JSON, Avro and Parquet. Technology EnvironmentThe role will involve working with a modern and evolving … should bring relevant experience and the ability to work across comparable technologies. Examples of technologies in scope include: Data processing and logic: ANSI SQL, Apache Spark, KafkaData formats: JSON, Avro, ParquetPlatforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQEngineering and deployment: CI/ ...

reconciliation and root-cause analysis.Experience building or supporting production data pipelines in a collaborative engineering environment.Experience working with distributed data processing frameworks such as Apache Spark.Working knowledge of common data formats such as JSON, Avro and Parquet.For More Experienced CandidatesStronger ownership of technical design across multiple datasets or pipeline … should bring relevant experience and the ability to work across comparable technologies.Examples of technologies in scope include:Data processing and logic: ANSI SQL, Apache Spark, KafkaData formats: JSON, Avro, ParquetPlatforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQEngineering and deployment: CI/CD tooling ...

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 ...

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 … 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 ...

Skills MUST HAVE: Strong hands-on experience with Quantexa implementation and development. Proven experience building and supporting big data platforms . Advanced knowledge of Apache Spark/PySpark . Strong programming skills in Scala and/or Python . Expertise in SQL and large-scale data modelling. Strong ...

large request volumes, large data volumes, or both.Deep expertise in distributed data systems: streaming (Kafka or similar), batch and ELT/ETL frameworks (Spark, Flink, dbt, Airflow or Argo Workflows), and modern lakehouse or warehouse technologies.Strong production Python experience and awareness of other relevant languages (Java/Kotlin) sufficient ...

Risk, XVA, CCR, FRTB, portfolio risk, fixed income analytics, securitised products, liquidity risk, or managed risk-as-a-service solutions. Familiarity with Snowflake, Databricks, Spark, AWS, Azure, Confluence, Azure DevOps, Git, Tableau, Power BI, message queues, or comparable tools and platforms. Knowledge of market data vendors, data mastering, golden ...