51 to 75 of 151 Hadoop Jobs in London

Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience building large-scale, high-throughput, 24x7 data systems - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience providing technical leadership and mentoring other engineers for best practices on data engineering Our inclusive culture empowers Amazonians to deliver the best results for our More ❯

cloud platforms (Azure, AWS, GCP) Hands-on experience with SQL, Data Pipelines, Data Orchestration and Integration Tools Experience in data platforms on premises/cloud using technologies such as: Hadoop, Kafka, Apache Spark, Apache Flink, object, relational and NoSQL data stores. Hands-on experience with big data application development and cloud data warehousing (e.g. Hadoop, Spark, Redshift, Snowflake More ❯

design of data architectures that will be deployed You have experience in database technologies including writing complex queries against their (relational and non-relational) data stores (e.g. Postgres, Apache Hadoop, Elasticsearch, Graph databases), and designing the database schemas to support those queries You have a good understanding of coding best practices & design patterns and experience with code & data versioning More ❯

collaborative skills to work with both technical and product teams. BASIC QUALIFICATIONS - 2+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience - 2+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience - 2+ years of developing and operating large-scale data … team or organization - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS PREFERRED QUALIFICATIONS - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with AWS Tools and Technologies (Redshift, S3, EC2) - Knowledge of software development life cycle or agile development environment with emphasis on BI practices Our inclusive More ❯

predictive modelling, machine-learning, clustering 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 ❯

sensitive data management (privacy, consent, encryption) Experience working with customer data platforms such as Salesforce or similar Excellent communication and stakeholder engagement skills Desirable: Exposure to big data tools (Hadoop, Spark, Kafka) Knowledge of integrating ML models and AI into data platforms Industry certifications (e.g. CDMP, AWS, Azure) Experience with data visualisation tools (Power BI, Tableau, Looker) This role More ❯

TB) data sets PREFERRED QUALIFICATIONS - Master's degree in statistics, data science, or an equivalent quantitative field - Experience using Cloud Storage and Computing technologies such as AWS Redshift, S3, Hadoop, etc. - Experience programming to extract, transform and clean large (multi-TB) data sets - Experience with AWS technologies Amazon is an equal opportunities employer. We believe passionately that employing a More ❯

Great experience as a Data Engineer Experience with Spark, Databricks, or similar data processing tools. Proficiency in working with the cloud environment and various software’s including SQL Server, Hadoop, and NoSQL databases. Proficiency in Python (or similar), SQL and Spark. Proven ability to develop data pipelines (ETL/ELT). Strong inclination to learn and adapt to new More ❯

Great experience as a Data Engineer Experience with Spark, Databricks, or similar data processing tools. Proficiency in working with the cloud environment and various software’s including SQL Server, Hadoop, and NoSQL databases. Proficiency in Python (or similar), SQL and Spark. Proven ability to develop data pipelines (ETL/ELT). Strong inclination to learn and adapt to new More ❯

years of relevant experience in several areas of Data Mining, Classical Machine Learning, Deep Learning, NLP and Computer Vision. Experience with Large Scale/Big Data technology, such as Hadoop, Spark, Hive, Impala, PrestoDb. Hands-on capability developing ML models using open-source frameworks in Python and R and applying them on real client use cases. Proficient in one More ❯

predictive modeling, machine-learning, clustering 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 ❯

of predictive modelling, machine learning, 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 ❯

visualization tools such as Tableau or Power BI (preferred but not required). Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud). Knowledge of big data tools (e.g., Hadoop, Spark). Certifications in data analytics or related fields (e.g., Microsoft Certified: Data Analyst Associate). Hiring Process: 15 min call with Talent Acquisition Technical Test Final interview with More ❯

You’ll Work With This business doesn’t do “just one stack”. You’ll be expected to work across a broad tech landscape: Big Data & Distributed Systems: HDFS, Hadoop, Spark, Kafka Cloud: Azure or AWS Programming: Python, Java, Scala, PySpark – you’ll need two or more, Python preferred Data Engineering Tools: Azure Data Factory, Databricks, Delta Lake, Azure More ❯

really make yourapplication stand out: Implementationexperience with Machine Learning models and applications Knowledgeof cloud-based Machine Learning engines (AWS, Azure, Google, etc.) Experiencewith large scale data processing tools (Spark, Hadoop, etc.) Abilityto query and program databases (SQL, No SQL) Experiencewith distributed ML frameworks (TensorFlow, PyTorch, etc.) Familiaritywith collaborative software tools (Git, Jira, etc.) Experiencewith user interface libraries/applications More ❯

e.g., SQL, PL/SQL, DDL, MDX, 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. - Knowledge of cloud services such as AWS or equivalent Our inclusive culture empowers Amazonians More ❯

task effort and identify dependencies. Excellent communication skills. Familiarity with Python and its data, numerical, and machine learning libraries. It would be great if you also had: Experience with Hadoop and Jenkins. Azure and AWS certifications. Familiarity with Java. What we do for you: At Leidos, we are passionate about customer success, united as a team, and inspired to More ❯

team! You will develop scalable data pipelines, ensure data quality, and support business decision-making with high-quality datasets. -Work across technology stack: SQL, Python, ETL, Big Query, Spark, Hadoop, Git, Apache Airflow, Data Architecture, Data Warehousing -Design and develop scalable ETL pipelines to automate data processes and optimize delivery -Implement and manage data warehousing solutions, ensuring data integrity More ❯

team! You will develop scalable data pipelines, ensure data quality, and support business decision-making with high-quality datasets. -Work across technology stack: SQL, Python, ETL, Big Query, Spark, Hadoop, Git, Apache Airflow, Data Architecture, Data Warehousing -Design and develop scalable ETL pipelines to automate data processes and optimize delivery -Implement and manage data warehousing solutions, ensuring data integrity More ❯

of leading a team and delivering projects with a commercial mindset. Prior experience with Event Sourcing (Kafka, Akka, Spark) and Data Distribution based architecture Experience with NoSQL (Mongo, Elastic, Hadoop), in memory (MEMSQL, Ignite) and relational (Sybase, DB2, SybaseIQ) data store solutions. Strong knowledge of data structures, algorithms, and design patterns Experience in data driven performance analysis and optimizations. More ❯

Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools (e.g. Matplotlib, Seaborn, Tableau) Desirable: - Exposure to cloud platforms (AWS, GCP, Azure) and big data tools (Hadoop, Spark) - MSc/PhD in Computer Science, AI, Data Science, or related field More ❯

. Strong knowledge of LLM algorithms and training techniques . Experience deploying models in production environments. Nice to Have: Experience in GenAI/LLMs Familiarity with distributed computing tools (Hadoop, Hive, Spark). Background in banking, risk management, or capital markets . Why Join? This is a unique opportunity to work at the forefront of AI innovation in financial More ❯

architectures. Experienced with Matillion and modern data visualisation tools (QuickSight, Tableau, Looker, etc.). Strong scripting and Linux/cloud environment familiarity. Desirable: Exposure to big data tools (Spark, Hadoop, MapReduce). Experience with microservice-based data APIs. AWS certifications (Solutions Architect or Big Data Specialty). Knowledge of machine learning or advanced analytics. Interested? This is a great More ❯

architectures. Experienced with Matillion and modern data visualisation tools (QuickSight, Tableau, Looker, etc.). Strong scripting and Linux/cloud environment familiarity. Desirable: Exposure to big data tools (Spark, Hadoop, MapReduce). Experience with microservice-based data APIs. AWS certifications (Solutions Architect or Big Data Specialty). Knowledge of machine learning or advanced analytics. Interested? This is a great More ❯

like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms like AWS, GCP, or Azure. Strong written and spoken English skills. Bonus Experience: Experience with big data tools (e.g., Hadoop, Spark) and distributed computing. Knowledge of NLP techniques and libraries. Familiarity with Docker, Kubernetes, and deploying machine learning models in production. Experience with visualization tools like Tableau, Power BI More ❯