9 of 9 Permanent Apache Spark Jobs in the City of London

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/ ...

proficiency in programming languages such as Python, Java, or Scala. Experience with cloud platforms like Azure. Knowledge of big data technologies such as Hadoop, Spark, or Kafka. Proficiency in SQL and database management systems. Familiarity with data warehousing concepts and tools. Ability to work collaboratively with cross-functional teams. ...

evaluation techniques. Cloud & MLOps: Experience with AWS, GCP, or Azure; Docker/Kubernetes; MLflow or similar tools. Data Handling: Familiarity with big data frameworks (Spark, Hadoop) and data versioning tools (DVC). Soft Skills: Strong problem-solving, communication, and ability to work in agile teams. Preferred Qualifications Experience with ...

Solid understanding of data warehousing, lakehouse and datalake architectures Familiarity with modern data engineering patterns (ETL/ELT, medallion architecture, observability) Experience working with Apache Spark and large-scale data processing For a full consultation on this exciting new role, please get in touch with ARC IT Recruitment ...

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 ...

Optimise data workflows for performance, cost efficiency, and maintainability using modern data-engineering tools and platforms (e.g., Azure Data Factory, AWS Data Pipeline, Databricks, Apache Spark). Support the integration of data into visualisation platforms and analytical environments (e.g., Power BI, ServiceNow). Ensure adherence to data governance ...

PyTorch, TensorFlow, JAX) Experience with scikit-learn, XGBoost, LightGBM Strong software engineering practices and clean code principles Data & Computing : Experience with big data technologies (Spark, Dask) SQL and NoSQL databases Cloud platforms (AWS, GCP, Azure) Experience Track record of successfully deployed ML models at scale Experience with time series ...

stores (Feast, AWS Feature Store). Containerisation (Docker) and orchestration (Kubernetes, ECS). Infrastructure as Code (Terraform, CloudFormation). Large-scale data processing frameworks (Spark, Dask). Familiarity with data governance and compliance frameworks. Experience in regulated industries such as healthcare or finance. Benefits: Competitive salary ...

fast-paced, challenging environment. Key Responsibilities: Design, implement, and debug ETL pipelines to process and manage complex datasets. Leverage big data tools, including Apache Kafka, Spark, and Airflow, to deliver scalable solutions. Collaborate with stakeholders to ensure data quality and alignment with business goals. Utilize programming expertise … experience in data engineering projects Good hands-on experience of designing, implementing, debugging ETL pipeline Expertise in Python, PySpark and SQL languages Expertise with Spark and Airflow Experience of designing data pipelines using cloud native services on AWS Extensive knowledge of AWS services like API Gateway, Lambda, Redshift, Glue ...