1 to 25 of 32 Hadoop Jobs in London

practices with Strong understanding of data modeling principles and techniques A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems. Knowledge of programming languages such as Python, R, or Java is beneficial. Knowledge of ETL/ELT processes (such as DBT), SQL, NoSQL ...

experience in data engineering roles, including 2+ years delivering Quantexa solutions Strong hands-on experience with Scala, Apache Spark, and Big Data frameworks (eg Hadoop, HDFS) Proven experience with core Quantexa capabilities: Data Ingestion Pipelines Entity Resolution configuration Scoring logic implementation Contextual Network generation Solid understanding of distributed systems ...

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 ...

energy sectors. Strong knowledge of data fabric architectures, metadata management, and data governance principles. Experience with SQL, ETL tools, and big data technologies (e.g., Hadoop, Spark, Kafka). Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and data integration frameworks. Strong problem-solving skills and ability to work ...

data modeling, schema design, normalization, and multidimensional modeling. - Experience with ETL/ELT tools (Glue, Informatica, Airflow). - Knowledge of Big Data technologies (Spark, Hadoop, Kafka). - Strong understanding of API-based integrations. Preferred Skills: - NoSQL experience (MongoDB, DynamoDB). - Snowflake/Redshift/Databricks exposure. - CI/ ...

familiarity with frameworks (e.g. Flask, Django) Experience building and orchestrating ETL pipelines (e.g. Airflow, Luigi, Argo) Exposure to big data technologies (e.g. Spark, Kafka, Hadoop) Experience working in Agile environments Solid understanding of data architecture and data quality best practices ...

familiarity with frameworks (e.g. Flask, Django) Experience building and orchestrating ETL pipelines (e.g. Airflow, Luigi, Argo) Exposure to big data technologies (e.g. Spark, Kafka, Hadoop) Experience working in Agile environments Solid understanding of data architecture and data quality best practices ...

information with attention to detail and accuracy. Adept at queries, report writing, and presenting findings. Experience working with large datasets and distributed computing tools (Hadoop, Spark, etc.) Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, etc.). Experience with data profiling tools and processes. ...

with both technical and non-technical stakeholders Nice to have: Experience with modern analytics and BI platforms. Knowledge of big data technologies (e.g. Spark, Hadoop). Experience with real-time or event-driven data architectures. Familiarity with data cataloguing and lineage tools. Experience in regulated or data-sensitive environments. ...

engage technical and non-technical stakeholders Nice to Have: Experience with modern analytics and BI platforms Knowledge of big data technologies (e.g. Spark, Hadoop) Experience with real-time or event-driven architectures Familiarity with data cataloguing and lineage tools Experience working in regulated or data-sensitive environments Relevant certifications ...

Machine Learning: TensorFlow, PyTorch, Scikit-learn GenAI/LLMs: OpenAI API, Hugging Face Transformers, LangChain, Langraph, RAG pipelines Data & Analytics: Pandas, NumPy, Spark, Databricks, Hadoop, Vector Databases, Snowflake Model Deployment: MLflow, FastAPI, Flask, Docker, Kubernetes Cloud & Infrastructure: AWS, Azure, GCP CI/CD pipelines (GitLab, Jenkins) Desirable Skills Experience ...

techniques, A/B testing methodologies, and experiment design. Solid background in ranking, recommendation, and retrieval systems. Familiarity with large-scale data tools (Hadoop, BigQuery, Amazon EMR, etc.). Experience with BI tools and visualization platforms such as Tableau, Qlik, or MicroStrategy. Bonus: Experience with geospatial data and advanced ...

Need: Experience in architecture & design and consulting services focused on enterprise solutions, data analytics platform, lake houses, data engineering, data processing, data warehousing, ETL, Hadoop & Big Data. Experience in BFSI Industry is required. Experience in defining and designing data governance, data management, and data security solutions for an enterprise ...

/Q or similar Experience with Airflow, Dagster or similar tools. Exposure to container technologies: Docker, Podman etc Knowledge of 'big data' technologies (Hadoop, Spark, Parquet) Experience with TAQ data, and exchange connectivity. Compensation Anticipated Salary Range for United States: $100,000 - $150,000 base salary, plus eligible ...

Cloud; Kubernetes and containerization. • AI Expertise: Advanced machine learning algorithms, GenAI models (e.g., GPT, BERT, DALL-E, GEMINI), NLP techniques. • Big Data: Experience with Hadoop and Spark. • Ethics: Knowledge of AI ethics and governance. • Methodologies: Agile and Scrum project management. Desired Skills & Experience • Deep knowledge of machine learning operations ...

setting technical standards and driving best practices across the organisation. The role demands hands-on expertise with Azure, big data technologies like Spark and Hadoop, and programming languages including Python. You will also oversee database architecture, data modelling, and ETL processes to ensure seamless integration across multiple platforms, using ...

DevOps and broader software engineering standards. Cloud experience (any platform). Previous mentoring experience. Nice to have: Snowflake or Databricks Spark, PySpark, Hadoop or similar big data tooling BI exposure (PowerBI, Tableau, etc.) Interview Process The process is fully structured, transparent, and efficient: Video call - high-level overview ...

DevOps and broader software engineering standards. Cloud experience (any platform). Previous mentoring experience. Nice to have: Snowflake or Databricks Spark, PySpark, Hadoop or similar big data tooling BI exposure (PowerBI, Tableau, etc.) Interview Process The process is fully structured, transparent, and efficient: Video call - high-level overview ...

PyTorch, TensorFlow, XGBoost, LightGBM Data Manipulation: Pandas, NumPy, LangGraph MLOps & Orchestration: MLflow, Apache Airflow Databases: Neo4j, MongoDB API Development: FastAPI Big Data (Beneficial): Apache Hadoop, Apache Spark (PySpark) What We Need From You 5-8 years of hands-on experience developing and deploying ML and/ ...

implement modern analytics solutions, including cloud platforms, AI, predictive modeling, and cognitive tools Oversee structured and unstructured data management systems, including relational, columnar, Hadoop, and NoSQL platforms Implement modern data visualisation platforms such as Tableau, Power BI, Qlik, or MicroStrategy Consult with clients to identify analytical opportunities, design solutions ...

support and migration experience Desirable knowledge and experience: AWS accreditation Knowledge of COTS products (including but not limited to; Elasticsearch, NiFi, Rabbit, Kafka, MongoDB, Hadoop, Ansible, Git and Kubernetes) Development of dashboards for monitoring and alerting through Grafana, Splunk, Prometheus and OpenText Om and Ops Bridge On prem ...

junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop). The Role As a Tech Lead , you will play a critical role in designing, building, and maintaining data pipelines and infrastructure that enable … junior & Mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop). Data Preparation: Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data ...

data solutions, with a focus on innovation, resilience, and regulatory compliance. Key Responsibilities: Lead and develop robust data engineering platforms leveraging technologies such as Hadoop, Spark, and Splunk. Design, implement, and maintain scalable ETL/ELT data pipelines for diverse data types, including raw, structured, semi-structured, and unstructured … industry groups and vendor interactions to influence and adopt emerging technologies and standards. Qualifications and Skills: Extensive experience with big data frameworks such as Hadoop, Spark, and Splunk. Strong scripting capabilities in Python, with experience in object-oriented and functional programming paradigms. Proven expertise in handling varied data formats ...

analytics Requirements : - Java + least one additional server-side language (e.g., Python, Go, Scala, etc.) - Experience with multiple data storage technologies (e.g., MySQL, Hadoop, Cassandra ) - Familiarity with AWS services (RDS, Step Functions, EC2, Kinesis) - Experience defining and upholding SLOs/KPIs and participating in architecture reviews - Skilled in testing ...

build a new on-prem data platform aligned to the metals strategy while developing and maintaining scalable data pipelines and analytics infrastructure. Using Hadoop, Big Data, and Spark technologies, you will ensure data quality through automated validation, monitoring, and testing. You will also enable seamless integration across data warehouses … Data technologies. Experience designing and building on-prem data platforms, from high-level architecture to detailed technical design. Hands-on experience configuring multi-node Hadoop clusters, including resource management, security, and performance tuning. Strong Big Data engineering background using Apache Airflow, Spark, dbt, Kafka, and Hadoop ecosystem tools. ...