1 to 25 of 237 Remote Apache Spark Jobs

Apache Spark Python AWS Cloud Data Pipelines A hands-on data engineering role within a large-scale cloud data programme, responsible for building, maintaining, and troubleshooting data pipelines using Apache Spark, PySpark, Apache Airflow, and a broad suite of AWS services. You will apply strong … complex, cloud-based data programme - designing, building, and maintaining data pipelines that process large volumes of data across a modern AWS-native stack. Using Apache Spark and PySpark for distributed data processing, Apache Airflow for orchestration, and a range of AWS services for storage, compute, and analytics ...

United Kingdom A hands-on data engineering role within a large-scale cloud data programme, responsible for building, maintaining, and troubleshooting data pipelines using Apache Spark, PySpark, Apache Airflow, and a broad suite of AWS services. You will apply strong analytical and engineering skills to deliver trusted … complex, cloud-based data programme - designing, building, and maintaining data pipelines that process large volumes of data across a modern AWS-native stack. Using Apache Spark and PySpark for distributed data processing, Apache Airflow for orchestration, and a range of AWS services for storage, compute, and analytics ...

data processing. In this role, you will architect and maintain production-grade data products and APIs, leveraging technologies such as Java/Scala, SQL, Spark, Airflow, and Kubernetes to deliver reliable, high-performance solutions. You will collaborate with cross-functional partners across Finance, Accounting, and Analytics to translate complex … clean, maintainable, and efficient code, ensuring adherence to best practices through code reviewsBig Data EngineeringDesign, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache AirflowOptimise data storage, retrieval, and processing systems to ensure reliability, scalability, and performanceDevelop and fine-tune complex queries using ...

platform at scale, ideally in a consumer or marketplace environment. Deep understanding of distributed systems and modern data ecosystems — including extensive experience with Databricks, Apache Spark, Apache Kafka, Apache Flink, Apache Beam and DBT. Demonstrated success in designing, building, and operating data platforms at scale ...

intersection of consulting, technology, innovation, and strategic alliances and you will bring deep expertise in the Databricks Data Intelligence Platform, Lakehouse architecture, Delta Lake, Apache Spark, Unity Catalog, MLflow, Mosaic AI, data engineering, machine learning, GenAI and cloud-native delivery. As a key leader within our AI & Data … translate business needs into Databricks-led solution designs, build prototypes and proof points. Shape end-to-end solutions using Databricks Intelligence Platform, Delta Lake, Apache Spark, Unity Catalog, Databricks Workflows, Delta Live Tables/Lakeflow-style pipelines, MLflow, Feature Store, Model Serving and Mosaic AI capabilities. Build, lead ...

intersection of consulting, technology, innovation, and strategic alliances and you will bring deep expertise in the Databricks Data Intelligence Platform, Lakehouse architecture, Delta Lake, Apache Spark, Unity Catalog, MLflow, Mosaic AI, data engineering, machine learning, GenAI and cloud-native delivery. As a key leader within our AI & Data … translate business needs into Databricks-led solution designs, build prototypes and proof points. • Shape end-to-end solutions using Databricks Intelligence Platform, Delta Lake, Apache Spark, Unity Catalog, Databricks Workflows, Delta Live Tables/Lakeflow-style pipelines, MLflow, Feature Store, Model Serving and Mosaic AI capabilities. Team Leadership ...

scalable application components, microservices, and data integration layers to support high-throughput regulatory reporting.Big Data Processing: Develop and optimize distributed data processing jobs using Apache Spark, Hadoop, and Hive to aggregate and transform large-scale financial datasets.Real-Time Streaming: Build and maintain real-time data ingestion and streaming … pipelines using Apache Kafka.Database Management: Design and optimize data models in MongoDB and relational databases, ensuring high performance for complex queries and data storage.Agile Execution: Drive sprint planning, task estimation, and daily progress within an Agile/Scrum framework to ensure timely delivery of project milestones.Requirement Translation: Partner closely ...

application components, microservices, and data integration layers to support high-throughput regulatory reporting. Big Data Processing: Develop and optimize distributed data processing jobs using Apache Spark, Hadoop, and Hive to aggregate and transform large-scale financial datasets. Real-Time Streaming: Build and maintain real-time data ingestion … streaming pipelines using Apache Kafka. Database Management: Design and optimize data models in MongoDB and relational databases, ensuring high performance for complex queries and data storage. Agile Execution: Drive sprint planning, task estimation, and daily progress within an Agile/Scrum framework to ensure timely delivery of project milestones. ...

should have specialist experience in one or more of the following technologies**Azure Databricks*** Design and build high-performance data pipelines: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services.* Experience of Databricks ML and Azure … develop predictive models and drive business insights.* Proven expertise in Databricks, Apache Spark, and data pipeline development and strong understanding of data warehousing concepts and practices.* Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks and Azure Data Factory.* Azure Data Engineer Associate and Databricks ...

help design and deliver cutting-edge data solutions for customers operating in some of the UK's most complex and challenging environments. Using Databricks, Apache Spark and cloud-native technologies, you’ll develop scalable Lakehouse architectures and production-grade data pipelines that enable organisations to trust, share … opportunity to grow your career while helping customers unlock the power of their data. Responsibilities Design, build and optimise scalable data pipelines using Databricks, Apache Spark, PySpark and Delta Lake. Develop and implement modern Lakehouse architectures, applying Medallion (Bronze, Silver, Gold) design principles to support trusted and reusable ...

Senior Data Engineer (Databricks) - London (Hybrid) - Up to £85,000 Databricks - Apache Spark - Delta Lake - Python - SQL - Azure We're partnering with a fast-growing technology business that's investing heavily in its data platform and engineering capability. This is an opportunity to join a highly collaborative team … progression within a growing technology business. Key Experience Required Proven experience as a Data Engineer within production environments. Strong hands-on experience with Databricks, Apache Spark, Delta Lake, Python, and SQL. Experience building and supporting scalable ETL/ELT pipelines. Strong understanding of distributed data processing and data ...

Generative AI initiatives by developing scalable, secure and reliable data platforms. Key Responsibilities Design, build and maintain high-throughput data pipelines using Apache Spark and cloud-native technologies. Develop scalable ETL/ELT workflows for structured and unstructured datasets. Build and optimise data-processing solutions within AWS environments. … standards. Troubleshoot complex data-processing and distributed-system issues within production environments. Essential Experience 5+ years of commercial Data Engineering experience. Strong hands-on Apache Spark development experience. Strong programming experience with Java and/or Scala. Strong AWS experience, ideally including technologies such as S3, EMR, Glue ...

frameworks, tools and applications that make that data available to other teams and systems. Your primary toolset in your work will be Java microservices, Spark/Scala data processing (also some Flink), Kubernetes and AWS native tooling.**What You'll Do:*** Write highly fault-tolerant Java code within Apache Spark to produce platform products used by our customers to query our event pipelines/ingestion for insight into active threat trends and related analytics* Design, develop, and maintain ultra-high-scale data platforms that process petabytes of data* Participate in technical reviews of our products and help ...

frameworks, tools and applications that make that data available to other teams and systems.Your primary toolset in your work will be Java microservices, Spark/Scala data processing (also some Flink), Kubernetes and AWS native tooling.What You'll Do: Write highly fault-tolerant Java code within Apache Spark … combined between backend/cloud development and data platform engineering roles5+ years of experience building data platform product(s) or features with (one of) Apache Spark, Flink or Iceberg, or with comparable tools in GCP5+ years of experience programming with Java, Scala or Kotlin.Proven experience utilizing AI technologies ...

knowledge of optimisation techniques for large‐scale data processing Strong proficiency in SQL and Python for handling complex data problems Hands‐on experience with Apache Spark (PySpark or Spark SQL) Experience with the Azure data stack Knowledge of workflow orchestration tools like Azure Data Factory or Apache … cost optimisation strategies for cloud data platforms Experience with data quality frameworks and implementation Experience with data visualisation tools like Power BI or Apache Superset Experience with other cloud data platforms like AWS, GCP or Oracle Experience with modern unified data platforms like Databricks or Microsoft Fabric Experience with ...

Modern data platforms: Databricks, Snowflake and cloud‐native data services Data architecture: Lakehouse, medallion, data mesh and domain‐oriented patterns Data processing: Apache Spark, SQL and distributed processing technologies Data storage: Delta Lake, Apache Iceberg and open table formats Data pipelines: Enterprise‐scale ETL/ELT, batch … streaming patterns Transformation and quality: dbt, Great Expectations and equivalent tooling Orchestration: Apache Airflow and cloud‐native orchestration services Event streaming: Kafka and cloud‐native event‐streaming technologies Data modelling: Dimensional, analytical and domain‐oriented modelling Data governance: Catalogue, metadata, lineage, quality, security, privacy and access controls Data products ...

Modern data platforms: Databricks, Snowflake and cloud-native data services Data architecture: Lakehouse, medallion, data mesh and domain-oriented patterns Data processing: Apache Spark, SQL and distributed processing technologies Data storage: Delta Lake, Apache Iceberg and open table formats Data pipelines: Enterprise-scale ETL/ELT, batch … streaming patterns Transformation and quality: dbt, Great Expectations and equivalent tooling Orchestration: Apache Airflow and cloud-native orchestration services Event streaming: Kafka and cloud-native event-streaming technologies Data modelling: Dimensional, analytical and domain-oriented modelling Data governance: Catalogue, metadata, lineage, quality, security, privacy and access controls Data products ...

Modern data platforms: Databricks, Snowflake and cloud-native data services Data architecture: Lakehouse, medallion, data mesh and domain-oriented patterns Data processing: Apache Spark, SQL and distributed processing technologies Data storage: Delta Lake, Apache Iceberg and open table formats Data pipelines: Enterprise-scale ETL/ELT, batch … streaming patterns Transformation and quality: dbt, Great Expectations and equivalent tooling Orchestration: Apache Airflow and cloud-native orchestration services Event streaming: Kafka and cloud-native event-streaming technologies Data modelling: Dimensional, analytical and domain-oriented modelling Data governance: Catalogue, metadata, lineage, quality, security, privacy and access controls Data products ...

wider stakeholders. Technical Environment Experience with some of the following technologies would be beneficial: Python SQL Cloud platforms – AWS, Azure or GCP Databricks Apache Spark/PySpark Kafka/event-driven architectures Airflow dbt Git/GitHub CI/CD Infrastructure as Code Modern data platforms and distributed ...

across the team and support the continued growth of Unifeye. What You'll Do Design and build scalable batch and streaming data pipelines using Spark and Databricks. Develop modern Lakehouse architectures using Delta Lake and Medallion (Bronze, Silver and Gold) design principles. Build robust ingestion frameworks from APIs, files … pipelines, deployment automation and infrastructure-as-code practices. What We're Looking For Essential Strong commercial experience building production-grade data pipelines using Apache Spark (PySpark preferred). Experience delivering modern data platforms using Databricks or an equivalent Spark-based platform. Strong SQL skills and experience with ...

platforms:AWS,Azureand GCP Modern data platforms:Databricks, Snowflake and cloud-native data services Data architecture:Lakehouse, medallion, datameshand domain-oriented patterns Data processing:Apache Spark,SQLand distributed processing technologies Data storage:Delta Lake, ApacheIcebergand open table formats Data pipelines:Enterprise-scale ETL/ELT,batchand streaming patterns … Transformation and quality:dbt, Great Expectations and equivalent tooling Orchestration:Apache Airflow and cloud-native orchestration services Event streaming:Kafka and cloud-native event-streaming technologies Data modelling:Dimensional,analyticaland domain-oriented modelling Data governance:Catalogue, metadata, lineage, quality, security,privacyand access controls Data products:Reusable, discoverable and well ...

delivery across a range of projects, including data analysis, extraction, transformation, and loading, data intelligence, data security and proven experience in their technologies (e.g. Spark, cloud-based ETL services, Python, Kafka, SQL, Airflow) You have experience in assessing the relevant data quality issues based on data sources & uses cases ...

strategic planningRequired Skills & ExperienceTechnical SkillsStrong proficiency in SQL and data modellingExcellent programming skills in Python, Scala, or JavaHands-on experience with distributed data frameworks (Spark, Hadoop)Experience with data pipelines and ETL toolsExpertise in at least one cloud platform:Azure (Synapse, Data Factory, Databricks)AWS (S3, Glue, Redshift, Lambda ...

common technical standards and ways of working, and presenting these to the community Here’s a snapshot of the technologies that we use: Scala Apache Spark Databricks Apache Parquet Azure Cloud Platform Azure DevOps (Test plans, Backlogs, Pipelines) GIT What we’re looking for We’d love ...

will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise in Databricks, Apache Spark, and Azure to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations.We … version control.* **Data Engineering Stack** Experience building pipelines using streaming frameworks, distributed processing engines and relational or analytical storage technologies. Examples include Kafka, Spark, PostgreSQL.* **Orchestration** Experience defining and running data workflows using modern orchestration frameworks. Examples include Airflow, Dagster or Prefect.* **Data Quality and Lineage** Familiarity with tools ...