1 to 25 of 32 Hadoop Jobs in Slough

and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with big data technologies (Spark, Hadoop) or real-time data streaming (Kafka) in the context of analytics projects. This demonstrates ability to manage projects dealing with large-scale data and More ❯

have: Hands-on experience with data warehouse and lakehouse architectures (e.g., Databricks, Snowflake, or similar). Experience with big data frameworks (e.g., Apache Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, or GCP). More ❯

roles, with 5+ years in leadership positions. Expertise in modern data platforms (e.g., Azure, AWS, Google Cloud) and big data technologies (e.g., Spark, Kafka, Hadoop). Strong knowledge of data governance frameworks, regulatory compliance (e.g., GDPR, CCPA), and data security best practices. Proven experience in enterprise-level architecture design More ❯

with SQL and database management systems (e.g., PostgreSQL, MySQL). Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data tools (e.g., Spark, Hadoop) is a plus. Prior experience in financial data analysis is highly preferred. Understanding financial datasets, metrics, and industry trends. Preferred Qualifications: Experience with API More ❯

Experience 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 More ❯

Engineering: Proficiency in developing and maintaining real-time data pipelines. Experience with ETL processes, Python, and SQL. Familiarity with big data technologies like Apache Hadoop and Apache Spark. MLOps & Deployment: Experience deploying and maintaining ML inference pipelines. Proficiency with Docker and Kubernetes. Familiarity with AWS cloud platform. The Perfect More ❯

lakehouse architectures. - Knowledge of DevOps practices, including CI/CD pipelines and version control (eg, Git). - Understanding of big data technologies (eg, Spark, Hadoop) is a plus. More ❯

TensorRT and Experience with NVIDIA GPU hardware and software stack Understanding of HPC and AI workloads. Familiarity with BigData platforms and technologies, such as Hadoop or Spark. More ❯

on data accuracy, quality, and reliability Desirable (Nice to Have): Background in defence, government, or highly regulated sectors Familiarity with Apache Kafka, Spark, or Hadoop Experience with Docker and Kubernetes Use of monitoring/alerting tools such as Prometheus, Grafana, or ELK Understanding of machine learning algorithms and data More ❯

database systems (e.g., PostgreSQL, MySQL) Exposure to cloud platforms such as AWS, Azure, or GCP Experience with big data tools such as Spark and Hadoop Previous experience working with financial data, including understanding of financial metrics and industry trends More ❯

technologies Technical Skills Advanced machine learning and deep learning techniques Natural language processing Time series analysis and forecasting Reinforcement learning Big data technologies (Spark, Hadoop) Cloud infrastructure and containerization (Docker, Kubernetes) Version control and CI/CD practices More ❯

and classification techniques, and algorithms Fluency in a programming language (Python, C,C++, Java, SQL) Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau More ❯

Unix/Linux environments and scripting • Familiar with data visualisation tools (e.g. QuickSight, Tableau, Looker, QlikSense) Desirable: • Experience with large-scale data technologies (Spark, Hadoop) • Exposure to microservices/APIs for data delivery • AWS certifications (e.g. Solutions Architect, Big Data Specialty) • Interest or background in Machine Learning This is More ❯

identifying and managing sales opportunities at client engagements An understanding of database technologies e.g. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. Hadoop, Mahout, Pig, Hive, etc.; An understanding of statistical modelling techniques e.g. Classification and regression techniques, Neural Networks, Markov chains, etc.; An understanding of cloud More ❯

clustering and classification techniques. Fluency in a programming language (Python, C, C++, Java, SQL). Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau). More ❯

Functions, Synapse, etc.). Advanced SQL skills, including performance tuning and query optimization. Strong Python programming skills. Experience with big data tools such as Hadoop, Spark, and Kafka. Proficiency in CI/CD processes and version control. Solid experience with Terraform and Infrastructure as Code (IaC). Experience with More ❯

modelling Excellent communication and stakeholder management skills Fluency in a Programming Language (C++ or Python) Familiarity with Big Data Frameworks and Visualisation tools (Cassandra, Hadoop, Spark, Tableau) Desirable: Experience within an AI/ML-focused team or projects Familiarity with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Exposure to More ❯

engineering capabilities Experience working with Big Data Experience of data storage technologies: Delta Lake, Iceberg, Hudi Knowledge and understanding of Apache Spark, Databricks or Hadoop Ability to take business requirements and translate these into tech specifications Competence in evaluating and selecting development tools and technologies Sound like the role More ❯

Java, with experience in AI frameworks (e.g., TensorFlow, PyTorch, Keras). Strong knowledge of data analysis, visualisation tools, and big data technologies (e.g., SQL, Hadoop, Spark). Experience with machine learning techniques, including NLP, recommendation algorithms, and computer vision. Familiarity with cloud platforms (Azure) for deploying AI solutions . More ❯

What we’re looking for Proven experience as a Data Engineer in cloud environments (Azure ideal) Proficiency in Python, SQL, Spark, Databricks Familiarity with Hadoop, NoSQL, Delta Lake Bonus: Azure Functions, Logic Apps, Django, CI/CD tools 💼 What you’ll get from Mars A competitive salary & bonus Hybrid More ❯

distributed systems Strong knowledge of Kubernetes and Kafka Experience with Git, and Deployment Pipelines Having worked with at least one of the following stacks: Hadoop, Apache Spark, Presto AWS Redshift, Azure Synapse or Google BigQuery Experience profiling performance issues in database systems Ability to learn and/or adapt More ❯

work hands-on in Python, R etc. The data scientist will work and collaborate with engineering teams to iteratively analyse data using Scala, Spark, Hadoop, Kafka, Storm etc. Experience with NoSQL databases and familiarity with data visualisation tools will be of great advantage. What will you experience in terms More ❯

analysis, preferably in IoT or related fields. Proficient in programming languages such as Python and SQL. Experience with big data tools and platforms (e.g. Hadoop/Snowflake, Spark, Azure IoT Hub, AWS IoT). Please apply to the advert for more information. More ❯

. Great expertise in designing/building/implementing complex data pipelines. Vast experience with Databricks. Strong knowledge of distributed computing frameworks e.g Spark, Hadoop ecosystem. Highly experienced with cloud-based data platform AWS. Solid programming skills with Python, Spark. Demonstrated ability to engineer/architect solutions for Big More ❯

haven’t been siloed in a big firm then don’t worry. Additional exposure to the following is desired : - Tech Stack you will learn Hadoop and Flink RUST, Javascript, React, Redux, Flow Linux, Jenkins Kafka, Avro, Kubernetes, Puppet Involvement in the Java community My client is based London. Home More ❯