51 to 75 of 701 Apache Spark Jobs in the UK

environments. Technical Skills: Experience building and operating ETL/ELT pipelines. Hands-on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with some of these or similar ...

operating ETL/ELT pipelines and large-scale data architectures. Hands-on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with similar technologies is essential).Ability ...

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 ...

through production deliveryCore Skills and ExperienceExperience in designing and implementing enterprise-scale data platforms.Strong hands-on experience with Databricks, including Delta Lake, Unity Catalog, Spark, Structured Streaming, and Lakehouse architectureStrong hands-on experience with Snowflake, including data modelling, performance optimisation, Snowpark, data sharing, and governance capabilitiesExpertise in Apache Spark, Python, SQL, and modern ELT/ETL frameworksProven ability to rapidly evaluate, prototype, and compare emerging technologies and architectural patternsExperience designing large-scale analytical platforms supporting high-volume and high-velocity datasetsStrong understanding of data architecture principles including dimensional modelling, Data Vault, Lakehouse methodologies, and distributed computingExperience ...

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 Reporting ...

.Relational Databases and Data Warehousing concepts.Enterprise ETL tools such as Informatica, Talend, Datastage or Alteryx.Project experience using the any of the following technologies: Hadoop, Spark, Scala, Oracle, Pega, Salesforce.Cross and multi-platform experience.Financial services sector experience.Line management experience.Team building and leading.Mentoring/staff development experience.#TalanUK #LI-HB1QualificationsYou must ...

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 ...

project objectives.Conduct code reviews and engineering quality assurance, promoting clean, maintainable, high-quality code and adherence to software engineering best practices.Optimise platform performance across Spark workloads, Delta Lake, data pipelines, storage, and compute to maximise scalability, reliability, and cost efficiency.Design and deliver enterprise-grade Machine Learning, Generative … platform architect, defining reference architectures, integration patterns, and target-state designs across enterprise Databricks environments.Deep expertise across Databricks including Delta Lake, Unity Catalog, Spark, PySpark, Databricks SQL, Databricks Workflows, Lakeflow, Lakehouse architecture, MLflow, AI/BI Genie, Mosaic AI, and Agent Bricks.Proven experience leading engineering teams across both onshore ...

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 experience ...

skills, with experience of Java or Scala beneficial Experience building large-scale ETL/ELT and data processing pipelines Hands‐on experience with Apache Spark and distributed data processing technologies Experience designing and operating cloud-native data platforms, particularly within AWS Familiarity with Docker, Kubernetes and CI/ ...

Python, Java or Scala, and SQL. Hands‐on experience building and operating large‐scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud‐native data ...

Python, Java or Scala, and SQL. Hands-on experience building and operating large-scale data pipelines using big data and distributed processing technologies (e.g. Apache Spark, Hadoop). Experience designing and maintaining data lakes, distributed storage platforms, and data pipeline orchestration tools. Experience working with cloud-native data ...

Data Warehousing concepts. Enterprise ETL tools such as Informatica, Talend, Datastage or Alteryx. Project experience using the any of the following technologies: Hadoop, Spark, Scala, Oracle, Pega, Salesforce. Cross and multi-platform experience. Team building and leading. Qualifications You must be: Willing to work on client sites, potentially ...

semi-structured, and unstructured dataHands-on expertise in containerization and orchestration using Docker and Kubernetes for scalable production systemsFamiliarity with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g., AWS, Azure, GCP), and analytics libraries (e.g., pandas, numpy, matplotlib)Exposure to DevOps, DataOps, and MLOps concepts and best practicesExperience ...

plusAbility to write clean, maintainable, scalable, and robust code in PythonFamiliarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP)Basic understanding or exposure to containerization technologies such as Docker and Kubernetes would be beneficialExposure to software engineering ...

Programming-related field* Experience influencing technical decisions and supporting capability growth.* Experience with CI/CD practices* Experience with big data tools e.g. Spark, Hadoop, NiFi* Exposure to infrastructure scaling e.g. Kubernetes* Exposure to Ansible and Terraform* Understanding of ML algorithms and deployment* Experience with SQL Server high-availability ...

operating ETL/ELT pipelines and large-scale data architectures. Hands-on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with similar technologies is essential). Ability ...

operating ETL/ELT pipelines and large‐scale data architectures. Hands‐on experience with modern data stacks — our tech includes Python, SQL, Snowflake, Apache Iceberg, AWS S3, PostgresDB, Airflow, dbt, and Apache Spark, deployed via AWS, Docker, and Terraform (experience with similar technologies is essential). Ability ...

continuous learning to understand new data management systems Strong proficiency in hands-on development using industry-standard tools and languages (e.g., SQL, Python, Spark, cloud platforms), with a commitment to code quality and delivery excellence Preferred qualifications, capabilities, and skills Hands-on experience with Databricks for scalable data engineering … analytics, and collaborative development, as well as proficiency in managing large datasets using Apache Iceberg for efficient, reliable table management and data lake optimization Experience architecting and implementing enterprise-scale data warehouses on cloud platforms (e.g., AWS, Azure, GCP), including migration from legacy systems Advanced proficiency in designing ...

processes. Technical Skills Programming: Proficiency in Python, Java, Scala, or similar languages. Big Data Technologies: Hands-on experience with big data tools e.g. (Databricks, Apache Spark, Hadoop). Cloud Platforms: Familiarity with AWS, Azure, GCP, or other cloud ecosystems for data engineering tasks. Expertise in relational databases (e.g. … postgres, sql server) Data Integration Tools: Knowledge of platforms like Airflow, Apache NiFi, or Talend. Data Storage and Modelling: Experience with data warehousing tools (e.g. Snowflake, Redshift, BigQuery) and schema design. Version Control and CI/CD: Familiarity with Git, Docker, and CI/CD pipelines for deployment. Experience ...