1 to 25 of 60 Remote Apache Spark Jobs

deliver reliable, high-performance data solutions using Databricks and modern cloud technologies. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and Delta Lake Build and optimize ETL/ELT workflows for batch and streaming data Develop data models to support analytics, reporting … data pipelines, architectures, and best practices Required Qualifications 3+ years of experience in data engineering or a similar role Strong experience with Databricks and Apache Spark Proficiency in Python and SQL Experience with Delta Lake, data modeling, and performance tuning Hands-on experience with cloud platforms (AWS, Azure ...

Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you. Role: Spark-Scala Developer Location: London Working Mode: Hybrid (Weekly 3 days onsite) Contract Type: Inside IR35 Duration: 12 months Rate: £440 per day Inside IR35 … Must have skills: -Spark & Scala Nice to have skills: -Spark Streaming, Hadoop, -Hive, -SQL, -Sqoop, - Impala Detailed Job Description: At least 8+ years of experience and strong knowledge in Scala programming language. Able to write clean, maintainable and efficient Scala code following best practices. Good knowledge ...

will initially be for 6 months. It is also fully remote. Key Responsibilities • Design, develop, and maintain batch and streaming data pipelines using Databricks (Apache Spark) • Build and optimize ETL/ELT workflows for large-scale structured and unstructured data • Implement Delta Lake architectures (Bronze/Silver/… Gold layers) • Integrate data from multiple sources (databases, APIs, event streams, files) • Optimize Spark jobs for performance, scalability, and cost • Manage data quality, validation, and monitoring • Collaborate with analytics and ML teams to support reporting and model development • Implement CI/CD, version control, and automated testing for data ...

team members, building technical expertise and capability Key Responsibilities Develop production-ready data pipelines and processing jobs using batch and streaming frameworks such as Apache Spark and Apache Beam Apply expertise in data storage technologies including relational, columnar, document, NoSQL, data warehouses, and data lakes Implement modern ...

team members, building technical expertise and capability Key Responsibilities Develop production-ready data pipelines and processing jobs using batch and streaming frameworks such as Apache Spark and Apache Beam Apply expertise in data storage technologies including relational, columnar, document, NoSQL, data warehouses, and data lakes Implement modern ...

team members, building technical expertise and capability Key Responsibilities Develop production-ready data pipelines and processing jobs using batch and streaming frameworks such as Apache Spark and Apache Beam Apply expertise in data storage technologies including relational, columnar, document, NoSQL, data warehouses, and data lakes Implement modern ...

team members, building technical expertise and capability Key Responsibilities Develop production-ready data pipelines and processing jobs using batch and streaming frameworks such as Apache Spark and Apache Beam Apply expertise in data storage technologies including relational, columnar, document, NoSQL, data warehouses, and data lakes Implement modern ...

development Backend development using Java and/or Scala Frontend development with Angular or similar JavaScript frameworks Experience with distributed compute technologies, such as: Apache Spark Databricks Apache Beam (or similar) Solid experience with Azure cloud technologies Database experience with cloud and relational databases, e.g. Snowflake, Sybase ...

while working on complex, real-world use cases. Key Responsibilities Design, develop, and optimise data ingestion pipelines and transformations within the Quantexa platform using Spark and Scala Configure and implement Quantexa components, including Entity Resolution, Scoring, and Network Generation, to meet specific use cases Collaborate with Solution Architects … Experience Quantexa Technical Certification (mandatory) 6+ years' experience in data engineering roles, including 2+ years delivering Quantexa solutions Strong hands-on experience with Scala, Apache Spark, and Big Data frameworks (eg Hadoop, HDFS) Proven experience with core Quantexa capabilities: Data Ingestion Pipelines Entity Resolution configuration Scoring logic implementation ...

platform, features, and best practices with Strong understanding of data modeling principles and techniques A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems. Knowledge of programming languages such as Python, R, or Java is beneficial. Knowledge of ETL/ELT processes ...

platform, features, and best practices with Strong understanding of data modeling principles and techniques A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems. Knowledge of programming languages such as Python, R, or Java is beneficial. Knowledge of ETL/ELT processes ...

Responsibilities will include; Design, implement, and optimize end-to-end solutions using Fabric components: o Data Factory (pipelines, orchestration) o Data Engineering (Lakehouse, notebooks, Apache Spark) o Data Warehouse (SQL endpoints, schemas, MPP performance tuning) o Real-Time Analytics (KQL databases, event ingestion) o Manage and enhance OneLake ...

Responsibilities will include; Design, implement, and optimize end-to-end solutions using Fabric components: o Data Factory (pipelines, orchestration) o Data Engineering (Lakehouse, notebooks, Apache Spark) o Data Warehouse (SQL endpoints, schemas, MPP performance tuning) o Real-Time Analytics (KQL databases, event ingestion) o Manage and enhance OneLake ...

Knowledge of machine learning frameworks (e.g., PySpark, PyTorch) and model deployment tools (e.g., MLflow, TensorFlow Serving). Strong experience with data processing frameworks (e.g., Apache Spark, Flink). Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra). Hands-on experience with cloud platforms (e.g. ...

projects. Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes using Azure Databricks, Data Factory, and other Azure services Implement and optimize Spark jobs, data transformations, and data processing workflows, Managing Databricks notebooks, Delta lake with Python, Delta Lake with Sparks SQL in Databricks Leverage Azure DevOps … data pipeline design. Experience with SQL, Python, and Spark. Excellent problem-solving and analytical skills. Effective communication and teamwork abilities. Skills Azure Databricks Python Apache Spark SQL ETL processes Data Warehousing Data Pipeline Design Cloud Architecture Performance Tuning ...

experience and familiarity with frameworks (e.g. Flask, Django) Experience building and orchestrating ETL pipelines (e.g. Airflow, Luigi, Argo) Exposure to big data technologies (e.g. Spark, Kafka, Hadoop) Experience working in Agile environments Solid understanding of data architecture and data quality best practices ...

experience and familiarity with frameworks (e.g. Flask, Django) Experience building and orchestrating ETL pipelines (e.g. Airflow, Luigi, Argo) Exposure to big data technologies (e.g. Spark, Kafka, Hadoop) Experience working in Agile environments Solid understanding of data architecture and data quality best practices ...

DataOps practices, including CI/CD, containerisation, and workflow orchestration Hands-on experience with ETL/ELT frameworks and big data tools (e.g. Spark, Airflow, Hive) Proficiency in programming languages such as Python, Java, and SQL Experience with SQL and NoSQL database design and optimisation Strong understanding of batch ...

platforms such as AWS, Azure, or GCP. Exposure to modern data tools such as Snowflake, Databricks, or BigQuery. Familiarity with streaming technologies (e.g., Kafka, Spark Streaming, Flink) is an advantage. Experience with orchestration and infrastructure tools such as Airflow, dbt, Prefect, CI/CD pipelines, and Terraform. What ...

transformation. Proficiency in Python and PySpark for advanced data engineering, machine learning, and large-scale distributed processing within Databricks. Hands-on experience with Spark optimizations (Adaptive Query Execution, caching, partitioning, broadcast joins) to deliver performant solutions for big data workloads. Advanced knowledge of BI and visualization tools such ...

solutions for high-volume analytics platforms Build and optimise ETL pipelines and data flows across Snowflake, Oracle, and distributed systems Process large datasets using Spark (Java or Scala) on AWS EMR Develop data-driven services and components using Java and/or Python Contribute to microservices-based architectures Deploy … data engineering roles Strong experience working with Snowflake and Oracle Solid engineering background in Java and/or Python Hands-on experience with Apache Spark (Java or Scala) Experience with AWS , including EMR and other core services Exposure to Docker and Kubernetes (EKS) Proven experience building scalable ...

years total experience Details Job Description: API development, cloud-native architectures, and Generative AI frameworks like LLaMA, Mistral etc. FastAPI, Unicorn, and Swagger Python, Apache Spark (PySpark), Kubernetes, Django Apache Kafka for real-time data streaming, and distributed computing frameworks. Experience in optimizing and deploying AI models ...

Azure or AWS Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure/AWS Data Engineering certifications Databricks certifications What ...

solutions.• Pipeline Development: Develop and configure meta-data driven data pipelines using data orchestration tools such as Azure Data factory and engineering tools like Apache Spark to ensure seamless data flow.• Monitoring and Failure Recovery: Implement monitoring procedures to detect failures or unusual data profiles and establish recovery ...

Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing (e.g., Spark, Dask). Qualifications & Experience Experience: 5+ years in a software or data engineering role, with at least 3 years specifically focused on the deployment and scaling ...