1 to 25 of 92 Remote Apache Spark Jobs

develop, and maintain end-to-end data pipelines using Ab Initio (GDE, PDL, Conduct>IT, Express>IT).Build scalable batch and streaming workloads using Apache Spark (PySpark/Scala).Develop and orchestrate data ingestion flows using Apache NiFi for real-time and near-real-time use cases.Optimize …/ELT jobs for scalability, throughput, and resource efficiency.Perform bottleneck analysis and tuning for Spark jobs, NiFi processors, and Ab Initio graphs.Demos and knowledge transfers to stakeholders around product developments.Spread your experience and knowledge to junior engineers.Improve automated testing and deployments using CI/CD pipelines.Expectation to line manage ...

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 ...

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 ...

data warehouses and data lakes. (Preferred)Experienced in data ingestion, processing, transformation, and delivery using batch, streaming, and real-time methods. (Preferred)Experience supporting Spark‐based platforms (e.g. EMR, Glue, Databricks) (Preferred)Proficient with DevOps tools and practices (Git, Jenkins, Docker, Kubernetes) as well as ETL frameworks (Apache Spark, Airflow, AWS IoT Analytics/Device Management/Events). (Preferred)Programming expertise in Python, Java, Scala, SQL, Spark, Unix shell scripting, and AWS CLI. (Preferred)Great background in building and managing AWS platforms for analytics and data lake workloads, including application and framework management. (Preferred ...

Testing Guild with common standards such as metrics and use of test tools 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 We'd love to hear from ...

platformsAdvanced Python and SQL skills, with experience in modern engineering practices such as CI/CD and TDDExperience with big data frameworks such as Apache Spark or similar technologiesSolid understanding of data modelling, data warehousing, OLTP and data lake architecturesExperience working with cloud ecosystems such as AWS, Azure ...

able to guide how one could deploy infrastructure into different environments. Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop. Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes) Ability to create ...

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 ...

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 ...

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 ...

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 ...

Experience with data warehousing concepts and technologies.Knowledge of other BI tools (e.g., Tableau, Looker) and data modelling techniques.Familiarity with big data technologies (e.g., Hadoop, Spark).Familiarity with modern data architecture (e.g., Data Mesh, Fabric).An understanding of infrastructure as code (e.g., Terraform)Experience with CI/CD pipelines ...

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 ...

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 ...

Architecture.- Strong programming skills in Python and SQL.- Familiarity with cloud platforms such as AWS, Azure, or GCP.- Knowledge of Snowflake and experience with Spark/PySpark.- Experience in designing and implementing modern data platform engineering solutions.If you are ready to make an impact within a dynamic team ...

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 ...

multidisciplinary team to support and enhance over 70 active BI products. What You'll Bring Essential Skills & Experience: Core Technologies: Azure Databricks (or similar Spark-based platforms) and Azure Data Factory (ADF). Languages: SQL and Python. Data Platforms: Azure Data Lake and SQL Server RDBMS. ETL Tools ...

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 ...

proficiency in SQL and database technologies Experience with programming languages such as Python, Java, or Scala Hands-on experience with data pipeline tools (e.g., Apache Airflow, Kafka) Familiarity with cloud platforms (AWS, Azure, Google Cloud) Understanding of data warehousing solutions (e.g., Snowflake, Redshift, BigQuery) Strong problem-solving and analytical … skills Preferred Skills Experience with big data technologies (e.g., Hadoop, Spark) Knowledge of data modeling techniques and schema design Familiarity with containerization tools (Docker, Kubernetes) Experience with CI/CD pipelines and DevOps practices Understanding of data security and compliance standards ...