1 to 25 of 88 Remote Apache Spark Jobs

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 ...

with Red Hat OpenShift and Ceph storage platforms. Programming experience (e.g. Python, JavaScript) Experience working with event streaming and data pipeline technologies (e.g. Kafka, Apache NiFi, Apache Spark). Experience delivering multi-system integration projects within defence, government, or highly regulated environments. Experience implementing and configuring training ...

Experience using Git/version control Strong communication skills with both technical and non-technical stakeholders Desirable Skills: Microsoft Fabric Azure Synapse Analytics Databricks Apache Spark/PySpark dbt Apache Airflow Power BI Azure DevOps CI/CD pipelines Terraform What's On Offer: £65k+ salary package ...

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 ...

engineers should be adept at Extract, Transform, Load (ETL) processes. This includes using frameworks such as the Medallion Architecture, as well as tools like Apache Airflow, Fivetran, Azure Data Factory, and Amazon Glue to automate data workflows and ensure data quality. Familiarity with cloud computing services, such … Cloud Platform, is increasingly important. Data engineers often leverage these platforms for scalable data storage and processing capabilities. Knowledge of big data frameworks like Apache Spark, Beam is crucial for handling large datasets and real-time data processing. Understanding data modelling techniques helps data engineers design efficient data ...

e.g., AWS, Azure, GCP) and their AI/ML services.Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL, data pipelines, and automated workflows for moving and processing data.Data Governance: Adherence to data governance, security, and privacy standards ...

Python, or similar languages relevant to data manipulation and scripting.Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL/ELT, data warehousing, and automated workflows for moving and processing data.Data Governance: Strong understanding and practical experience with ...

maintain scalable Databricks pipelines (ETL, streaming, ML workflows).• Perform cluster and job performance tuning: optimize cluster sizing, caching, partitioning, and shuffle management.• Monitor Spark job metrics, analyze logs, and identify bottlenecks in data throughput or latency.• Implement cost-optimization strategies for Databricks jobs and clusters using autoscaling … using Databricks REST APIs, Prometheus, or Azure Monitor.• Maintain best practices for data engineering performance, testing, and documentation.Technical Skills Required• Strong proficiency with Databricks, Apache Spark (SQL, PySpark, Scala), and Delta Lake.• Deep understanding of Spark execution plans, shuffle optimization, and data partitioning strategies.• Experience tuning ...

with the Lead Data Engineer and partnering with data science, analytics and product teams. Key responsibilities * Build and maintain scalable data pipelines using Databricks, Apache Spark and Delta Lake * Develop and optimise batch and streaming workflows for reliability and performance * Contribute to lakehouse architecture and medallion pattern implementation … optimisation opportunities * Translate business requirements into technical solutions * Contribute to documentation and continuous improvement Required experience * Strong experience delivering production grade Databricks pipelines * Strong Spark, Delta Lake and Databricks Workflows experience * Python and SQL proficiency * Experience on Azure data platforms such as Azure Data Factory, ADLS Gen2, Azure DevOps ...

engineering best practices Skills & Experience * 3+ years' commercial experience in Data Engineering * Strong Java or Python development skills * Experience with Kafka, Flink or Spark * Experience building ETL/ELT or streaming data pipelines * Knowledge of AWS (Azure or GCP also considered) * Experience with Docker, Kubernetes and CI/ ...

Have:Certifications: Google Cloud or AWS Certified Solutions Architect certification.ETL and Data Pipeline Expertise: Experience with ETL tools and Hadoop-based technologies (e.g., Spark) and/or batch/streaming data pipelines such as Beam and Flink.Data Architecture: Proven ability in designing and building data lake and data warehouse ...

e.g., AWS, Azure, GCP) and their AI/ML services.Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL, data pipelines, and automated workflows for moving and processing data.Data Governance: Adherence to data governance, security, and privacy standards ...

Python, or similar languages relevant to data manipulation and scripting.Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL/ELT, data warehousing, and automated workflows for moving and processing data.Familiarity with data modelling techniques (e.g., dimensional, relational) and data ...

Company descriptionCompany DescriptionPublicis Media harnesses the power of modern media through leading agency brands Dysrupt, Infinite Roar, Publicis Collective, Publicis Health Media, Spark Foundry, Starcom and Zenith, as well as global accelerator PMX; immersive experience group PMCI and access to integrated platform-based technologies and offerings from CJ, Epsilon … across 20+ marketing platforms.Build and optimize schemas, transformations, and ETL logic for high-performance, reusable data workflows.Contribute directly to the DFP codebase (Python, SQL, Spark) — developing pipelines and infrastructure alongside the engineering team.Establish data versioning, testing, and governance frameworks ensuring reliability, lineage, and compliance.Data Engineering LeadershipDrive best practices ...

optimising ETL/ELT pipelines. Strong understanding of Lakehouse, Data Warehouse, and Data Lake architectures. Experience with Azure Data Factory, Azure Synapse, and Apache Spark. Knowledge of data modelling, semantic models, and enterprise reporting solutions. Experience implementing data governance, security, and quality frameworks. Strong understanding of modern data engineering ...

architecture (SQL and NoSQL) Experience with cloud technologies Experience with cloud platforms Experience with CI/CD practices Experience with big data tools e.g. Spark, Hadoop, NiFi Experience managing direct reports, providing regular guidance and performance feedback Ability to create delivery plans with estimated timelines for personal and team ...

architecture (SQL and NoSQL) Experience with cloud technologies Experience with cloud platforms Experience with CI/CD practices Experience with big data tools e.g. Spark, Hadoop, NiFi Experience managing direct reports, providing regular guidance and performance feedback Ability to create delivery plans with estimated timelines for personal and team ...

large request volumes, large data volumes, or both.Deep expertise in distributed data systems: streaming (Kafka or similar), batch and ELT/ETL frameworks (Spark, Flink, dbt, Airflow or Argo Workflows), and modern lakehouse or warehouse technologies.Strong production Python experience and awareness of other relevant languages (Java/Kotlin) sufficient ...

/continuous delivery (CI/CD) pipelines, containerisation, and workflow orchestration.Familiar with ETL/ELT frameworks, and experienced with Big Data Processing Tools (e.g. Spark, Airflow, Hive, etc.)Knowledge of programming languages (e.g. Java, Python, SQL)Hands-on experience with SQL/NoSQL database design.Degree in STEM, or similar ...

continuous delivery (CI/CD) pipelines, containerisation, and workflow orchestration. Familiar with ETL/ELT frameworks, and experienced with Big Data Processing Tools (e.g. Spark, Airflow, Hive, etc.) Knowledge of programming languages (e.g. Java, Python, SQL) Hands-on experience with SQL/NoSQL database design. Degree in STEM ...

Server, Oracle, Snowflake, Databricks).Experience with data integration (ETL/ELT, APIs).Familiarity with cloud data platforms (AWS, Azure, GCP) and big data (Hadoop, Spark, Kafka) a plus.Domain Knowledge:Exceptional understanding of the Funds business lifecycle, financial instruments, market data, and investment operations.In-depth knowledge of regulatory reporting ...

native architectures.Hands-on experience with Python, SQL and modern software engineering practices.Experience building large-scale batch and streaming data solutions using technologies such as Spark, Kafka, Flink, Beam or equivalent.Deep knowledge of modern data architectures including data warehouses, data lakes and lakehouse platforms.Strong understanding of analytical data modelling, dimensional ...

PostgreSQL (or similar relational databases) and NoSQL databases. Experience with vector databases such as Qdrant, Milvus or pgvector . Familiarity with technologies such as Apache Spark, Airflow, Kafka, Elasticsearch/OpenSearch, Pandas and Polars . Strong understanding of data modelling, storage architecture and performance optimisation. Desirable Experience working ...

driven decision making. What you'll be doing Building and optimising scalable data pipelines using Java (primary) and technologies like Kafka, Flink, or Spark Developing real-time streaming solutions and event-driven architectures using AWS services (Kinesis, MSK, Lambda, Glue) Contributing to data architecture, modelling, and best practices across ...

prompt/version control, and Responsible AI/MRM complianceEnterprise AI Integration & DataAPI- and event-driven integration of AI into enterprise workflowsData platforms: Databricks, Spark, Snowflake; streaming via KafkaBackend & Distributed SystemsLanguages: Python (expert), Java/Spring Boot (enterprise standard), Go (plus)Architecture: Microservices, domain-driven design, event-driven systemsAPIs ...