76 to 100 of 466 Apache Spark Jobs in England

in commodities markets or broader financial markets. Knowledge of quantitative modeling, risk management, or algorithmic trading. Familiarity with big data technologies like Kafka, Hadoop, Spark, or similar. Why Work With Us? Impactful Work: Directly influence the profitability of the business by building technology that drives trading decisions. Innovative Culture More ❯

in commodities markets or broader financial markets. Knowledge of quantitative modeling, risk management, or algorithmic trading. Familiarity with big data technologies like Kafka, Hadoop, Spark, or similar. Why Work With Us? Impactful Work: Directly influence the profitability of the business by building technology that drives trading decisions. Innovative Culture More ❯

processes in the engineering delivery cycle including Agile and DevOps, Git, APIs, Containers, Microservices and Data Pipelines. Experience working with one or more of Spark, Kafka, or Snowflake My client have very limited interview slots and they are looking to fill this vacancy within the next 2 weeks. I More ❯

automation. Proficiency in building and maintaining batch and streaming ETL/ELT pipelines at scale, employing tools such as Airflow, Fivetran, Kafka, Iceberg, Parquet, Spark, Glue for developing end-to-end data orchestration leveraging on AWS services to ingest, transform and process large volumes of structured and unstructured data More ❯

environments with AI/ML components or interest in learning data workflows for ML applications . Bonus if you have e xposure to Kafka, Spark, or Flink . Experience with data compliance regulations (GDPR). What you can expect from us: Opportunity for annual bonuses Medical Insurance Cycle to More ❯

statistics, computer science, mathematics, or a related quantitative field - Experience with scripting languages (e.g., Python, Java, R) and big data technologies/languages (e.g. Spark, Hive, Hadoop, PyTorch, PySpark) PREFERRED QUALIFICATIONS - Master's degree, or Advanced technical degree - Knowledge of data modeling and data pipeline design - Experience with statistical More ❯

Argo, Dagster or similar. Skilled with data ingestion tools like Airbyte, Fivetran, etc. for diverse data sources. Expert in large-scale data processing with Spark or Dask. Strong in Python, Scala, C# or Java, cloud SDKs and APIs. AI/ML expertise for pipeline efficiency, familiar with TensorFlow, PyTorch More ❯

strong grasp of modern cloud architectures.?Expertise in data pipelines, ETL/ELT, and working with structured & unstructured data.?Strong skills in SQL, Python, Spark, or other relevant technologies.?Prior exposure to Microsoft Fabric is a huge plus -- but if you're eager to learn, we'll get you … repositories. 7. Document data architecture, processes, and workflows for reference and knowledge sharing. 8. Utilise programming languages (e.g., C#, Python, SQL) and technologies (e.g., Apache Spark, SSIS, .NET) to manipulate and analyse data. 9. Participate in code reviews, version control (e.g., using Git), and other software development best More ❯

experience in data engineering, with a strong understanding of modern data technologies (e.g., cloud platforms like AWS, Azure, GCP, and data tools such as Apache Spark, Kafka, dbt, etc.). Proven track record of leading and managing data engineering teams in a consultancy or similar environment. Strong expertise More ❯

experience in data engineering, with a strong understanding of modern data technologies (e.g., cloud platforms like AWS, Azure, GCP, and data tools such as Apache Spark, Kafka, dbt, etc.). Proven track record of leading and managing data engineering teams in a consultancy or similar environment. Strong expertise More ❯

in a data-focused role, with a strong passion for working with data and delivering value to stakeholders. Strong proficiency in SQL, Python, and Apache Spark , with hands-on experience using these technologies in a production environment. Experience with Databricks and Microsoft Azure is highly desirable. Financial Services More ❯

design principles for usability, maintainability and extensibility Experience working with Git in a version-controlled environment Good knowledge of parallel computing techniques (Python multiprocessing, Apache Spark), and performance profiling and optimisation Good understanding of data structures and algorithms An enthusiastic problem-solving mindset with a desire to solve More ❯

availability. Very strong technical background leading application development - with experience in some or all of the following technologies: Python, Java, Spring Boot, TensorFlow, PyTorch, Apache Spark, Kafka, Jenkins, Git/Bitbucket, Terraform, Docker, ECS/EKS, IntelliJ, JIRA, Confluence, React/Typescript, Selenium, Redux, Junit, Cucumber/Gherkin. More ❯

Utilise Azure Databricks and adhere to code-based deployment practices Essential Skills: Over 3 years of experience with Databricks (including Lakehouse, Delta Lake, PySpark, Spark SQL) Strong proficiency in SQL with 5+ years of experience Extensive experience with Azure Data Factory Proficiency in Python programming Excellent stakeholder/client More ❯

MSSQL, PostgreSQL, MySQL, NoSQL Cloud: AWS (preferred), with working knowledge of cloud-based data solutions Nice to Have: Experience with graph databases, Hadoop/Spark, or enterprise data lake environments What You’ll Bring Strong foundation in computer science principles (data structures, algorithms, etc.) Experience building enterprise-grade pipelines More ❯

MSSQL, PostgreSQL, MySQL, NoSQL Cloud: AWS (preferred), with working knowledge of cloud-based data solutions Nice to Have: Experience with graph databases, Hadoop/Spark, or enterprise data lake environments What You’ll Bring Strong foundation in computer science principles (data structures, algorithms, etc.) Experience building enterprise-grade pipelines More ❯

building ETL pipelines - Experience with SQL - Experience mentoring team members on best practices PREFERRED QUALIFICATIONS - Experience with big data technologies such as Hadoop, Hive, Spark, EMR - Experience operating large data warehouses Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our More ❯

transitions from legacy to cloud-based environments. Ensure data integrity, security, and compliance with financial industry regulations. Build and optimize ETL processes using Databricks, Spark, and other data processing tools. Implement data governance best practices within the Databricks environment, including data quality, access controls, and audit logging. Develop real More ❯

HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell) PREFERRED QUALIFICATIONS - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Our inclusive culture empowers Amazonians to deliver the best results for More ❯

related industries. Certification in relevant areas (e.g., AWS Certified Data Analytics, Google Data Analytics Professional Certificate). Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure). Experience with data visualization design principles and storytelling techniques. Knowledge of agile methodologies and project management. Strategic More ❯

the big 3 cloud ML stacks (AWS, Azure, GCP). Hands-on experience with open-source ETL, and data pipeline orchestration tools such as Apache Airflow and Nifi. Experience with large scale/Big Data technologies, such as Hadoop, Spark, Hive, Impala, PrestoDb, Kafka. Experience with workflow orchestration … tools like Apache Airflow. Experience with containerisation using Docker and deployment on Kubernetes. Experience with NoSQL and graph databases. Unix server administration and shell scripting experience. Experience in building scalable data pipelines for highly unstructured data. Experience in building DWH and data lakes architectures. Experience in working in cross More ❯

Azure or AWS 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/AWS Data Engineering certifications Databricks certifications What More ❯

Azure or AWS 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/AWS Data Engineering certifications Databricks certifications What More ❯

methods for synthesis prediction using tools like PSI4 , Orca , or Gaussian . Big Data : Experience curating and processing data from diverse sources; exposure to Apache Spark or Hadoop is beneficial. Cloud Platforms : Proficiency with AWS , GCP , or Azure . ML Frameworks : Hands-on with scikit-learn , TensorFlow , PyTorch More ❯

of object-oriented design principles for usability and maintainability Experience with Git in a version-controlled environment Knowledge of parallel computing techniques (Python multiprocessing, Apache Spark) and performance optimization Understanding of data structures and algorithms Problem-solving mindset with enthusiasm for tackling technical challenges Ability to communicate complex More ❯