1 to 25 of 89 Remote Apache Spark Jobs

Engineer with an Azure focus, you 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. Skills/Experience 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. Develop and maintain secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data. Build and deploy AI/ML models: Integrate Machine … and best practices with a focus on how AI can support you in your delivery work Solid experience as a Data Engineer or similar role. 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 More ❯

an Azure and Databrick focus, you 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. Duties Design and build high … performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Design and oversee the delivery of secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data. Abilty to Design, Build and deploy AI/… to ensure successful data platform implementations. Your Skills and Experience Solid experience as a Data Architect with experience in designing, developing and implementing Databricks solutions Proven expertise in Databricks, Apache Spark, and data platforms with a strong understanding of data warehousing concepts and practices. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks, and Azure More ❯

an Azure and Databrick focus, you 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. Duties Design and build high … performance data platforms: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Design and oversee the delivery of secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data. Abilty to Design, Build and deploy AI/… to ensure successful data platform implementations. Your Skills and Experience Solid experience as a Data Architect with experience in designing, developing and implementing Databricks solutions Proven expertise in Databricks, Apache Spark, and data platforms with a strong understanding of data warehousing concepts and practices. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks, and Azure More ❯

Job Accountabilities Develop robust, scalable data pipelines to serve the easyJet analyst and data science community. Highly competent hands-on experience with relevant Data Engineering technologies, such as Databricks, Spark, Spark API, Python, SQL Server, Scala. Work with data scientists, machine learning engineers and DevOps engineers to develop, develop and deploy machine learning models and algorithms aimed at … indexing, partitioning. Hands-on IaC development experience with Terraform or CloudFormation. Understanding of ML development workflow and knowledge of when and how to use dedicated hardware. Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data … e.g. access management, data privacy, handling of sensitive data (e.g. GDPR) Desirable Skills Experience in event-driven architecture, ingesting data in real time in a commercial production environment with Spark Streaming, Kafka, DLT or Beam. Understanding of the challenges faced in the design and development of a streaming data pipeline and the different options for processing unbounded data (pubsub More ❯

experience in a leadership or technical lead role, with official line management responsibility. Strong experience with modern data stack technologies, including Python, Snowflake, AWS (S3, EC2, Terraform), Airflow, dbt, Apache Spark, Apache Iceberg, and Postgres. Skilled in balancing technical excellence with business priorities in a fast-paced environment. Strong communication and stakeholder management skills, able to translate More ❯

an AI Engineer, you will be responsible for designing and developing intelligent agents capable of autonomous decision-making in distributed environments. You will leverage your expertise in Python and Spark to process large-scale data and use modelling techniques to enable complex agentic behaviours. Experience working with MCP servers or similar distributed computing platforms is key. Key Responsibilities: Design … and develop agentic AI systems that operate autonomously across diverse data sources and workflows. Implement scalable data processing pipelines using Apache Spark and Python. Build, train, and fine-tune advanced AI/ML models for agent reasoning, planning, and execution. Integrate solutions with MCP (Massively Concurrent Processing) servers or equivalent architectures. Work closely with data engineers, researchers, and … Skills & Experience: 4+ years of experience in AI/ML engineering or data-intensive systems. Strong proficiency in Python for AI, ML, and data engineering tasks. Deep experience with Apache Spark (PySpark or Scala-based implementations). Solid understanding and hands-on experience with modelling intelligent agents, including symbolic, neural, or hybrid approaches. Experience deploying to and managing More ❯

field. Technical Skills Required • Hands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD). • Experience with Apache Spark or any other distributed data programming frameworks. • Comfortable writing efficient SQL and debugging on cloud warehouses like Databricks SQL or Snowflake. • Experience with cloud infrastructure like AWS … Skills • Hands-on development experience in an airline, e-commerce or retail industry • Experience in event-driven architecture, ingesting data in real time in a commercial production environment with Spark Streaming, Kafka, DLT or Beam. • Experience implementing end-to-end monitoring, quality checks, lineage tracking and automated alerts to ensure reliable and trustworthy data across the platform. • Experience of More ❯

plus work experience BS & 5+ years of work experience MS & 4+ years of work experience Proficient with machine learning and statistics Proficient with Python, deep learning frameworks, Computer Vision, Spark Have produced production level algorithms Proficient in researching, developing, synthesizing new algorithms and techniques Excellent communication skills Desirable Qualifications Master's or PhD level degree 5+ years of work More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns More ❯

with AWS Cloud-native data platforms, including: AWS Glue, Lambda, Step Functions, Athena, Redshift, S3, CloudWatch AWS SDKs, Boto3, and serverless architecture patterns Strong programming skills in Python and Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns More ❯

platform. Candidate Profile: Proven experience as a Data Engineer, with strong expertise in designing and managing large-scale data systems. Hands-on proficiency with modern data technologies such as Spark, Kafka, Airflow, or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. More ❯

platform. Candidate Profile: Proven experience as a Data Engineer, with strong expertise in designing and managing large-scale data systems. Hands-on proficiency with modern data technologies such as Spark, Kafka, Airflow, or dbt. Strong SQL skills and experience with cloud platforms (Azure preferred). Solid programming background in Python, Scala, or Java. Knowledge of data warehousing solutions (e.g. More ❯

databases to power segmentation, recommendation, targeting, and measurement. Strong knowledge of both SQL and NoSQL databases like PostgreSQL, BigQuery, Cassandra, or DynamoDB. Experience with large-scale data platforms (e.g., Spark, Kafka, Flink, BigQuery) and cloud environments, with a preference for AWS or GCP . Expertise in data engineering: pipelines , modeling, batch vs. event streaming, and ETL/ELT. Demonstrated More ❯

driven decision-making. Responsibilities for the Senior Data Engineer: Design, build, and maintain scalable data pipelines and architectures, ensuring reliability, performance, and best-in-class engineering standards Leverage Databricks, Spark, and modern cloud platforms (Azure/AWS) to deliver clean, high-quality data for analytics and operational insights Lead by example on engineering excellence, mentoring junior engineers and driving … customer data Continuously improve existing systems, introducing new technologies and methodologies that enhance efficiency, scalability, and cost optimisation Essential Skills for the Senior Data Engineer: Proficient with Databricks and Apache Spark, including performance tuning and advanced concepts such as Delta Lake and streaming Strong programming skills in Python with experience in software engineering principles, version control, unit testing More ❯

skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if you're More ❯

skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me a copy of your CV if you're More ❯

having resided in the UK for at least the past 5 years and being a UK national or dual UK national. Experience in prominent languages such as Python, Scala, Spark, SQL. Experience working with any database technologies from an application programming perspective - Oracle, MySQL, Mongo DB etc. Experience with the design, build and maintenance of data pipelines and infrastructure More ❯

/Starburst Enterprise/Galaxy administration and CLI operations Container Orchestration : Proven track record with Kubernetes/OpenShift in production environments Big Data Ecosystem : Strong background in Hadoop, Hive, Spark, and cloud platforms (AWS/Azure/GCP) Systems Architecture : Understanding of distributed systems, high availability, and fault-tolerant design Security Protocols : Experience with LDAP, Active Directory, OAuth2, and More ❯

/Starburst Enterprise/Galaxy administration and CLI operations Container Orchestration : Proven track record with Kubernetes/OpenShift in production environments Big Data Ecosystem : Strong background in Hadoop, Hive, Spark, and cloud platforms (AWS/Azure/GCP) Systems Architecture : Understanding of distributed systems, high availability, and fault-tolerant design Security Protocols : Experience with LDAP, Active Directory, OAuth2, and More ❯

Skills Strong experience with Azure data services (Data Factory, Synapse, Blob Storage, etc.). Proficiency in SQL for data manipulation, transformation, and performance optimisation. Hands-on experience with Databricks (Spark, Delta Lake, notebooks). Solid understanding of data architecture principles and cloud-native design. Experience working in consultancy or client-facing roles is highly desirable. Familiarity with CI/ More ❯

Skills Strong experience with Azure data services (Data Factory, Synapse, Blob Storage, etc.). Proficiency in SQL for data manipulation, transformation, and performance optimisation. Hands-on experience with Databricks (Spark, Delta Lake, notebooks). Solid understanding of data architecture principles and cloud-native design. Experience working in consultancy or client-facing roles is highly desirable. Familiarity with CI/ More ❯

/ELT pipelines , data modeling , and data warehousing . Experience with cloud platforms (AWS, Azure, GCP) and tools like Snowflake, Databricks, or BigQuery . Familiarity with streaming technologies (Kafka, Spark Streaming, Flink) is a plus. Tools & Frameworks: Airflow, dbt, Prefect, CI/CD pipelines, Terraform. Mindset: Curious, data-obsessed, and driven to create meaningful business impact. Soft Skills: Excellent More ❯

Development Opportunities Enhanced Maternity & Paternity Charity Volunteer Days Cycle to work scheme And More.. DATA ENGINEER – ESSTENTIAL SKILLS Proven experience building data pipelines using Databricks . Strong understanding of Apache Spark (PySpark or Scala) and Structured Streaming . Experience working with Kafka (MSK) and handling real-time data . Good knowledge of Delta Lake/Delta Live Tables More ❯

and delivering end-to-end AI/ML projects. Nice to Have: Exposure to LLMs (Large Language Models), generative AI , or transformer architectures . Experience with data engineering tools (Spark, Airflow, Snowflake). Prior experience in fintech, healthtech, or similar domains is a plus. More ❯

Python and SQL Hands-on experiences with Data Architecture, including: Cloud platforms and orchestration tools (e.g. Dagster, Airflow) AI/MLOps: Model deployment, monitoring, lifecycle management. Big Data Processing: Spark, Databricks, or similar. Bonus: Knowledge Graph engineering, graph databases, ontologies. Located in London And ideally you... Are a zero-to-one builder who thrives on autonomy and ambiguity. Are More ❯