451 to 475 of 569 Apache Spark Jobs in the UK

experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP) Working knowledge of distributed data systems: Apache SparkTM, Delta Lake, or equivalent (Hadoop, Kafka, Flink) Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews Familiarity with one or more: data engineering … Engineering, or a quantitative discipline (or equivalent experience) Nice to Have: Databricks certification or experience with the Databricks Platform Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow Background at a data/AI company, cloud provider, or technical consulting firm Interview Process: Recruiter Screen → Hiring Manager Screen ...

DescriptionRole –Senior Databricks ArchitectTechnology – Databricks (Spark, PySpark/SQL) and data lake architecturesLocation – London, UKCompensation – Competitive (including bonus)Job DescriptionWe are looking for a Data Architect to design, build, and operate scalable data pipelines and data products, enabling a modern data mesh architecture. The role focuses on integrating legacy … systems with cloud-native platforms to support analytics, reporting, and domain-owned data products. Primary Skills Strong experience with Databricks (Spark, PySpark/SQL) and data lake architectures. Hands-on experience with streaming technologies, especially Kafka/Confluent Kafka. Experience integrating legacy data sources such as DB2 (mainframe ...

Help shape the technical roadmap for data engineering across Elliptic. Leverage and deploy AI and agentic systems to operate more effectively. Tech environment Scala | Spark | Databricks | AWS | Airflow | Kubernetes | Terraform | Functional Programming You will thrive here if you Enjoy end‐to‐end ownership, from writing the code to architecture … programming. Ability to design, build, and maintain distributed data systems in a cloud‐based environment. Hands‐on experience with big data frameworks such as Spark or Databricks. Knowledge of cloud infrastructure (AWS, GCP, or Azure). Judgement to balance scalability, performance, and maintainability. Experience with data modelling and workflow ...

domain data (bets, offers, rewards, digital data) into reusable, well‐defined datasets for downstream consumption. Implement data transformation logic using modern tooling (e.g. dbt, Spark, SQL‐based frameworks), ensuring consistency and testability. Build and optimise streaming data pipelines (Kafka/Flink or equivalent) to enable near real‐time data … maintaining scalable data platforms. Strong SQL and data modelling skills, with experience designing analytical datasets. Experience with modern data stack tools (e.g. dbt, Spark, Airflow, or similar orchestration and transformation frameworks). Experience with cloud‐based data platforms, ideally AWS. Understanding of medallion architecture or similar data layering approaches. ...

platform capabilities for data ingestion, transformation, orchestration, and processing across batch and real-time workloads. Own the integration strategy across tools such as dbt, Spark and Beam Lead the implementation and adoption of data quality, observability, security, testing and deployment including creating and sharing standards Partner closely with Analytics … supporting others Hands on experience transitioning to an AI-native Data Engineering landscape A strong Python and SQL engineer with experience using dbt, Spark and Terraform Strong experience working with GCP (or a comparable cloud platform), Infrastructure as Code, and CI/CD practices. Deep understanding of data storage ...

shared platform capabilities for data ingestion, transformation, orchestration, and processing across batch and real-time workloads. Own the integration strategy across tools such asdbt, Spark and Beam Lead the implementation and adoption of data quality, observability, security, testing and deployment including creating and sharing standards Partner closely with Analytics … excellence, and supporting others Hands on experience transitioning to an AI-native Data Engineering landscape A strong Python and SQL engineer with experience usingdbt, Spark and Terraform Strong experience working with GCP (or a comparable cloud platform), Infrastructure as Code, and CI/CD practices. Deep understanding of data ...

appropriate technologies for scalable analytics, trading strategy development, tick or time-series data, workflow automation and AI/ML-enabled use cases. Prefer Databricks, Spark and modern lakehouse patterns for scalable analytics where suitable, while recognising transferable experience with Snowflake and other enterprise data platforms. Ensure delivery choices balance … define OKRs, shape roadmaps and deliver enterprise data or analytics products. Hands-on understanding of data technologies and modern analytics platforms, preferably Databricks/Spark and lakehouse patterns; Snowflake experience is relevant and transferable but Databricks experience is preferred. Experience with Python, SQL and production analytics workflows; familiarity with ...

appropriate technologies for scalable analytics, trading strategy development, tick or time-series data, workflow automation and AI/ML-enabled use cases. Prefer Databricks, Spark and modern lakehouse patterns for scalable analytics where suitable, while recognising transferable experience with Snowflake and other enterprise data platforms. Ensure delivery choices balance … define OKRs, shape roadmaps and deliver enterprise data or analytics products. Hands-on understanding of data technologies and modern analytics platforms, preferably Databricks/Spark and lakehouse patterns; Snowflake experience is relevant and transferable but Databricks experience is preferred. Experience with Python, SQL and production analytics workflows; familiarity with ...

Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one Deep experience with distributed computing with Apache SparkTM and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models … data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache SparkTM, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits ...

Good to Have Knowledge of the adTech space and particularly the identifiers used in the field. Experience with large-scale distributed data processing (e.g., Apache Spark) and cloud data infrastructure across GCP and AWS (e.g., Dataproc, Dataflow, GKE, EMR). Experience with Temporal #J-18808-Ljbffr ...

Citi is hiring a Big Data Applications Support Analyst to monitor and troubleshoot a large-scale data platform built on Hadoop, Hive, Spark, and Kafka. You will work with global teams to ensure 24/7 availability and data integrity for business reporting. Ideal candidates have strong Linux ...

SaaS, cloud-native environment. You will build and guide a team, collaborate with partners and delivery leads, and drive innovative data pipelines using Hive, Spark, and Hadoop across multiple cloud platforms. #J-18808-Ljbffr ...

service capabilities, and supporting analytics across the business. You will drive the implementation of data lakes, warehouses, and real-time streams using Kafka, Flink, Spark, Iceberg and cloud-native practices with Kubernetes/OpenShift. #J-18808-Ljbffr ...

ideal candidate will have more than 10 years of experience in backend development and data platform engineering, with strong expertise in Java and Apache Spark. The role offers competitive compensation and benefits, reflecting the company's commitment to employee well-being. #J-18808-Ljbffr ...

regulations, and implement AI-driven automation while ensuring scalable, reliable data processing across big data stacks. The role emphasizes real-time streaming with Kafka, Spark-based batch processing, and close collaboration with Compliance to translate complex rules into robust software solutions. #J-18808-Ljbffr ...

Applied NLP and computer vision techniques Deployed AI models to production environments Implemented deep learning frameworks (TensorFlow, PyTorch) Worked with big data platforms (Hadoop, Spark) Collaborated with software developers for AI solutions Ensured scalability and performance of AI systems Documented model architecture and results Monitored deployed AI models ...

focusing on backend systems for large‐scale data storage, streaming, and warehousing. Experience with database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and query engines (Trino, Presto, Snowflake). Track record of mentoring and leading teams in successful projects. Excellent communication ...

engineering multi-site fail-over solutionsCandidates Must Have:4 years commercial Linux CentOS or Debian administration experiencePuppet configuration management or equivalent automation experienceHadoop/Spark Experience of security standards, best practices and principles. Strong scripting in at least one language ideally Ruby, PythonMaven, JenkinsMonitoring and alerting in Sensu/ ...

years of experience in business intelligence or data analytics. Experience with explaining technical analysis to stakeholders. Experience with big data technologies (e.g., Hadoop, Spark, Python, or R). About the job YouTube's Intelligence and Scaled Insights team analyzes content risks across social media to inform critical decision-making ...

related to building large-scale data storage, streaming, and warehousing systems. Experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.). Show a track record of mentoring and leading teams ...

years of experience in business intelligence or data analytics. Experience with explaining technical analysis to stakeholders. Experience with big data technologies (e.g., Hadoop, Spark, Python, or R). About the job YouTube’s Intelligence and Scaled Insights team analyzes content risks across social media to inform critical decision-making ...

related to building large-scale data storage, streaming, and warehousing systems. Experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.).Show a track record of mentoring and leading teams ...

raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.WHO WE AREWe’re building a founding team of Enterprise Account ...

research ideas to productionTrack record of promoting statistical rigour and experimental best practice across a teamPrior experience with large datasets and distributed computing (e.g. spark, hadoop or other map-reduce tech)Experience working in a fast-moving tech company or startupThis is a full-time role based ...

society's experience with software. Come join one of the fastest-growing startups, supported by best-in-class institutions like Battery Ventures, Salesforce Ventures, Spark Capital and Meritech. Pendo Core Values: Bias to Act, Hone Your Craft, The Team is Pendo, and Maniacal Focus. Location: Pendo is a hybrid ...