15 of 15 Apache Spark Jobs in Central London

data sets can be effectively combined and analysed. They can also utilise programming languages such as Python, Java or SQL and tools such as Apache Spark or in this instance LakeFS, for data processing and management. Useful - R, Apache Spark Very useful - Python, SQL, JSON, LakeFS. ...

warehousing, and data governance frameworks. Define and enforce best practices, security standards, and performance optimization across Databricks workloads. Design scalable big data architectures leveraging Spark, Delta Live Tables, Unity Catalog , and MLflow. Lead cloud architecture design on Azure/AWS/GCP (based on organization need) integrated with Databricks. … years overall experience in data engineering or data architecture. 5+ years of hands-on architecture experience specifically in Databricks . Expert in Apache Spark , PySpark , Databricks SQL , Delta Lake, and distributed systems. Strong understanding of Lakehouse architecture , BI ecosystems, and modern data platforms. Cloud expertise in Azure/ ...

logic into high-quality code using Python, Scala, or Java. Innovation: Evaluate and implement new technologies across Cloud (Azure, AWS, GCP) and Big Data (Spark, Kafka) stacks. Collaboration: Work closely with business teams to define data flows and ensure security protocols (encryption/authentication) are met. Technical Toolkit Languages ...

analytics environments. Knowledge of additional AWS services such as S3, Lambda, Athena, Kinesis, EMR, Fargate, or API Gateway. Experience with big data technologies including Spark, Databricks, Hadoop, or Dask. Familiarity with data visualisation tooling such as Plotly. Experience mentoring junior engineers or leading technical initiatives. What You’ll Receive ...

models are always running, always accurate, and always improving. Key Responsibilities ML Pipeline Orchestration & Automation Own and extend Circadia’s ML pipeline orchestration using Apache Airflow, including training, evaluation, and deployment workflows. Build and maintain automated pipelines for model retraining, validation, and promotion across development, staging, and production environments. … closely related infrastructure role. Strong proficiency in Python for ML pipeline development, tooling, and automation. Hands-on experience with ML pipeline orchestration tools, particularly Apache Airflow. Experience with model registries and experiment tracking platforms (MLflow preferred). Experience deploying and operating ML workloads on AWS (Batch ...

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 ...

auditable, lineage-aware, idempotent, and resilient in regulated environments. Implement robust data quality controls including testing, validation, monitoring, and alerting. Drive performance optimization across Spark and Snowflake workloads. Partner with Product, Engineering, DevOps, and Regulatory teams to translate requirements into scalable technical designs. Improve engineering standards, processes, and tooling ...

security controls. Monitor, maintain and optimise data platforms to ensure performance and reliability. Skills and Experience Required: ETL development using Python or similar languages Apache Spark, NiFi, or Kafka Relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra) databases AWS and cloud-based data services Palantir Foundry Stakeholder Engagement ...

validation experience across large datasets. Experience testing integrations with other Salesforce products (Sales Cloud, Service Cloud, Marketing Cloud). Exposure to big data technologies (Spark, Databricks, Snowflake, etc.). Excellent problem-solving skills and ability to work in fast-paced delivery environments. Strong communication and documentation skills. Desirable Experience ...

preparation. Machine learning and statistical methods, including model validation. Data analytics and visualisation techniques. Processing large datasets using batch or streaming tools such as Apache Spark. Data acquisition and fusion approaches. Cloud platforms (ideally AWS) and cloud-based data science solutions. DataOps principles and practices. Structured and unstructured databases. ...

data models and outputs Set up monitoring and ensure data health for outputs What we are looking for Proficiency in Python, with experience in Apache Spark and PySpark Previous experience with data analytics softwares Ability to scope new integrations and translate user requirements into technical specifications What ...

influence within the team and communicate clearly with technical and non-technical stakeholders. Data Engineer (New Technology/Microsoft) Strong experience with Databricks (Spark, PySpark, Delta Lake, and Unity Catalog advantageous). Proficiency in Azure data services (Azure Data Factory, Data Lake, Azure Functions advantageous). Experience contributing … Engineer or Solutions Architect certification (desirable). Databricks Certified Data Engineer or Machine Learning Associate (desirable). Experience with streaming solutions (Kafka, Event Hubs, Spark Streaming) (desirable). Knowledge of machine learning and AI on Databricks (desirable). Benefits of working at Canada Life We believe in recognising ...

team Exposure to sectors such as defence, public sector and consumer/retail Familiarity with modern data and AI tooling such as Python, Spark, Databricks, Azure cloud, and Generative AI platforms (experience with specific tools is helpful but not essential) A mix of technical, product and operational experience – comfortable ...

data sets can be effectively combined and analysed. They can also utilise programming languages such as Python, Java or SQL and tools such as Apache Spark or in this instance LakeFS, for data processing and management. Useful - R, Apache Spark. Very useful - Python, SQL, JSON, LakeFS. Reasonable ...

models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. ...