1 to 25 of 63 Apache Spark Jobs in London

Data Engineer 6 Month Contract Location: London (Onsite 4 days a week) Rate: £700 - £800 per day (INSIDE IR35) Skills: Python, Azure, Kubernetes, Apache Airflow, Apache Spark, DV Clearance We are looking to recruit a DV Cleared Data Engineer for a leading technology consultancy. This will … Work across Azure environments on the low side Support data engineering workloads within Kubernetes environments on the high side Develop and maintain workflows using Apache Airflow Work with Apache Spark for large-scale data processing Support the ongoing development and improvement of established data pipelines Help ensure ...

related disciplines within enterprise environments 4+ years of hands-on experience designing and implementing solutions on the Databricks Lakehouse Platform Strong expertise in Apache Spark, SQL, Python, Delta Lake, and modern data engineering practices Experience building and optimizing Extract, Transform, Load and Extract, Load, Transform data pipelines … solutions on the Databricks Lakehouse Platform. Design and implement scalable data and analytics solutions leveraging Databricks technologies Build, maintain, and optimize data pipelines using Apache Spark, SQL, Python, and Delta Lake Develop governed datasets and data products that support reporting, analytics, and artificial intelligence initiatives Partner with business ...

control (Git) and related software lifecycle tooling.Experience with tooling for monitoring, logging and alerting e.g. Splunk, New Relic or Grafana.Experience of technologies such as Apache Spark, Databricks, Snowflake, or BigQuery to transform big-data optimised for Tesco scaleExperience building solutions that run in the cloud, ideally Azure.Experience with … control (Git) and related software lifecycle tooling.Experience with tooling for monitoring, logging and alerting e.g. Splunk, New Relic or Grafana.Experience of technologies such as Apache Spark, Databricks, Snowflake, or BigQuery to transform big-data optimised for Tesco scaleExperience building solutions that run in the cloud, ideally Azure.Experience with ...

hands-on Senior Databricks Solutions Architect to support a complex, high-performance data platform within a global organisation. Youll design and optimise Spark workloads, build production streaming pipelines and deliver scalable Databricks solutions using Delta Live Tables, Workflows, Unity Catalog, Python, PySpark, Terraform and Databricks Asset Bundles. Key requirements … Advanced Apache Spark and Spark SQL optimisation Production Spark Structured Streaming experience Deep Databricks platform knowledge Strong Python and PySpark engineering capability Delta Live Tables, Workflows and Unity Catalog Terraform and Databricks Asset Bundles CI/CD and GitHub Actions Ability to work autonomously ...

Skills & Experience Data Engineering & Cloud Extensive experience designing, building and operating production data platforms using Azure Databricks and Azure. Strong hands-on expertise with Apache Spark, PySpark, Spark SQL and Delta Lake. Experience implementing and managing Unity Catalog, including governance, lineage and access controls. Proven delivery ...

Flask, Tornado or Django, Docker Experience working with ETL pipelines is desirable e.g. Luigi, Airflow or Argo Experience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. Data acquisition and development of data sets and improving data quality Preparing data for predictive and prescriptive modelling Hands ...

within either Flask, Tornado or Django, DockerExperience working with ETL pipelines is desirable e.g. Luigi, Airflow or ArgoExperience with big data technologies, such as Apache Spark, Hadoop, Kafka, etc. Data acquisition and development of data sets and improving data qualityPreparing data for predictive and prescriptive modellingHands on coding ...

modern frameworksWorking knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least oneDeep experience with distributed computing with Apache Spark and knowledge of Spark runtime internalsFamiliarity with CI/CD for production deploymentsWorking knowledge of MLOps, ML/AI models ...

while collaborating with the Data & Analytics Lead, technical colleagues and business stakeholders. Experience in the following areas would also be useful: Materialised Lake Views Apache Spark or Python. Power BI semantic modelling. APIs and cloud business system integration. Data governance, lineage and quality frameworks. Professional services experience. What ...

Excellent Python and SQL Solid grasp of data modelling, warehousing and lakehouse concepts Hands-on with orchestration (e.g. Airflow, Dagster) and distributed processing (e.g. Spark) Experience with cloud data platforms (AWS, Azure or GCP) and containerised deployment (Docker, Kubernetes) Good engineering practice: version control, CI/CD, testing ...

Senior Data Engineer: Passion for building scalable, resilient cloud data platforms Strong experience with Databricks or Snowflake on AWS Proven Python skills, including Spark and Airflow expertise Advanced SQL skills and end-to-end data modelling experience Experience building batch and real-time data integrations Hands-on CICD skills ...

. Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon). Familiarity with data lake architectures and distributed processing frameworks (e.g., Spark, Hadoop). Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines. Understanding of data governance, security, and compliance frameworks. Exposure ...

Advanced experience operating Delta tables at scale, covering transaction semantics, schema evolution, partitioning, and compaction, alongside highly optimised analytical query execution using DuckDB or Apache Spark.• Production-grade relational database expertise, particularly PostgreSQL (query tuning, indexing, partitioning, replication, and schema design across OLTP and analytics).• Strong KDB experience ...

Skills & Experience Strong commercial experience in data engineering within cloud-based environments. Advanced Python and SQL development skills. Hands-on experience with Azure Databricks, Apache Spark and PySpark. Good understanding of Delta Lake, lakehouse architecture and modern data modelling. Experience building and managing production data pipelines, including batch ...

requiredDo not rule yourself out if you do not have these. They are a bonus, not a checklist. Experience with Delta Lake, Iceberg, Spark or Databricks, PalantirExperience optimising LLM serving with tools such as vLLM, TGI or TensorRT LLMSearch and ranking experience. For example Elasticsearch or rerankersBackground in time ...

migration strategies as well as with machine learning, LLMs, and agentic AI workflows. Proficient in programming, debugging, and problem-solving using SQL, Python, Apache Spark, cloud platforms, and Lakehouse architectures and with AI tools. Experience collaborating with Global System Integrators (GSIs) and third-party consulting organizations to drive ...

Ingestion projects in Azure environment. Demonstrated analytical and problem-solving skills particularly those that apply to a big data environment. Experience on Python scripting, Spark SQL PySpark is a plus. We use generative AI tools to support our candidate screening process. This helps us ensure a fair, consistent ...

production rather than for novelty. You don't need to know all of it on day one. Data and compute: S3, Athena, Spark on EMR, SQLOrchestration and MLOps: Airflow, MLflow, Docker, ECS, Terraform, GitHub Actions for CI/CDModels: foundation models served through Amazon BedrockAgents: LangGraph for orchestration, deployed ...

experience building, deploying, and scaling AI/ML solutions using frameworks and platforms such as Scikit-learn, PyTorch, TensorFlow, Hugging Face, LangChain, Databricks, Spark, vector databases, cloud services (AWS/Azure), and MLOps tools including MLflow and Kubeflow. Proven ability to develop production-grade, large-scale AI systems with ...

experience with the SQL Server platform and T-SQL querying. Familiarity with cloud data platforms (e.g., AWS, Azure) and big data technologies (e.g., Kafka, Spark, Databricks, Snowflake).Expert-level knowledge of building ETL processes in Python. Expert-level knowledge of performance tuning and optimization in a Python/ ...

Applying advanced techniques in LLMs, agentic systems, vector databases, fine-tuning, and deployment tools (e.g., HuggingFace, Langchain).Hands-on experience working with Distributed Spark based systemsExperience with data engineering concepts or a good understanding of data engineering concepts Pre-sales or post-sales experience working with external clients across … variety of industry markets. Minimum of 5+ years of customer-facing experience would be preferred[Preferred] Experience working with Apache Spark to process large-scale distributed datasetsCommunication: Proven ability to communicate and teach complex technical concepts to both technical and non-technical audiences. Core Traits: Passion for lifelong ...

Maintain the controls and records needed to support auditing, data traceability and compliance requirements. Performance and operational management Investigate and improve the performance of Spark workloads, Delta tables and SQL compute. Review resource consumption and identify ways to reduce unnecessary platform and cloud expenditure. Set up monitoring and alerting … knowledge sharing and mentoring across the team. What we are looking for Practical experience managing Databricks in a production environment. A strong understanding of Apache Spark, Delta Lake and Unity Catalog. Experience working with one or more major cloud providers, including storage, networking and identity management. Confidence using ...

experience in software engineering, MLOps, and deploying machine learning models at scale. Proficiency in SQL, Python, and familiarity with big data technologies (e.g., Kafka, Spark) and/or cloud platforms (e.g., GCP, AWS, or Azure). Industry knowledge: Experience in gaming or digital entertainment is a strong plus. This ...

time ML & reproducibility: A strong grasp of production inference patterns and reproducible environments (Docker, MLflow or equivalent). Cloud & tooling: AWS, plus SageMaker, Snowflake, Spark/Databricks and Kubernetes. Engineering mindset: A focus on reliability, maintainability and continuous improvement. ...

data modelling skillsExperience with agentic AI coding tools (Claude Code, Copilot Agent Mode, Devin) and spec-driven developmentBig data/Lakehouse (Snowflake), ETL pipelines (Spark, Glue), or event streaming (Kafka)Interest in investment banking or financial instrumentsABOUT GOLDMAN SACHSAt Goldman Sachs, we commit our people, capital and ideas ...