1 to 25 of 29 Remote Apache Spark Jobs

Apache Spark Python AWS Cloud Data Pipelines A hands-on data engineering role within a large-scale cloud data programme, responsible for building, maintaining, and troubleshooting data pipelines using Apache Spark, PySpark, Apache Airflow, and a broad suite of AWS services. You will apply strong … complex, cloud-based data programme - designing, building, and maintaining data pipelines that process large volumes of data across a modern AWS-native stack. Using Apache Spark and PySpark for distributed data processing, Apache Airflow for orchestration, and a range of AWS services for storage, compute, and analytics ...

you. You'll be joining a large-scale cloud data transformation programme, helping design, build and optimise enterprise data platforms using Python, Databricks and Spark within a modern Lakehouse environment. Key Responsibilities Design, develop and maintain scalable data pipelines using Python and Databricks. Build, optimise and support enterprise …/ELT workflows using Apache Spark and Delta Lake. Design and develop robust data models and Lakehouse architectures. Implement and manage data workflows within the Databricks ecosystem. Ensure high levels of data quality, governance and pipeline reliability. Optimise performance across large-scale distributed data processing platforms. Collaborate with ...

designing and delivering modern data platforms, working closely with clients and technical teams to build scalable, secure and high-performing solutions using Databricks, Apache Spark and cloud technologies. You'll also play a key role in pre-sales activities, solution design, and helping to drive strategic Databricks initiatives … Databricks and modern data platform delivery. Skills & Experience Required 7+ years' experience in Data Architecture or Solution Architecture. Strong commercial experience with Databricks and Apache Spark . Experience delivering enterprise data platforms on AWS, Azure or GCP. Strong understanding of data warehousing, data lakes and lakehouse architectures. Experience ...

design and deliver scalable, enterprise-grade data solutions. This role will focus on building and optimising modern data platforms using Python, Databricks and Spark, enabling advanced analytics, reporting and data-driven innovation across the business. Client Details Our client is a leading international financial institution with a long-established … complex global environment. Description Design, build and maintain scalable data pipelines using Python and Databricks Develop and optimise ETL/ELT processes leveraging Spark and Delta Lake Create robust data models and data architectures within modern Lakehouse environments Implement and manage data workflows across the Databricks ecosystem Ensure data ...

seeking an experienced Lead Data Engineer with deep expertise in Python, Databricks and Spark to lead the delivery of large-scale data engineering initiatives. This is a unique opportunity for a technical leader who enjoys combining hands-on engineering with project delivery, team leadership and stakeholder engagement … similar hands-on leadership role Strong hands-on expertise in Python Extensive experience with Databricks, including workflows, notebooks and Delta Lake Strong experience with Apache Spark/PySpark Experience building and optimising enterprise-scale ETL pipelines Strong understanding of modern data architecture and Lakehouse concepts Advanced ...

lead quality assurance and testing activities within a large-scale cloud data engineering programme operating across a modern AWS-native technology ecosystem, including Apache Airflow, Amazon Athena, AWS Glue, S3, EMR, DynamoDB, and related cloud services. This role combines hands-on technical leadership with test strategy ownership . … reconciliation, and performance under load Oversee PySpark-based data validation and interrogation activities on AWS EMR Support testing and monitoring of workflows orchestrated through Apache Airflow Drive root cause analysis for production data issues and platform defects Risk Management & Reporting Identify, assess, and communicate quality risks across releases ...

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 ...

strategic thinking. Essential Skills & Experience Strong Microsoft Fabric expertise (Lakehouse, Warehouse, Pipelines, Notebooks) OneLake architecture and management Advanced SQL/T-SQL PySpark and Spark optimisation Data warehousing, modelling and ETL/ELT development Power BI semantic modelling Experience delivering enterprise cloud data platforms Experience integrating multiple business systems ...

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 ...

data models and ETL processes, to support the construction of scalable and efficient data systems. Familiarity with big data tools like DuckDB, Polars or Apache Spark for processing out-of-memory datasets" . Proven experience collaborating with first-team stakeholders within a professional sports environment, demonstrating strong interpersonal ...

prem environments. Hard Skills Experience in data engineering, ideally aerospace/defence or industrial sectors. ETL/ELT tools (Airflow, Azure, Microsoft SSIS), streaming (Spark, Kafka). Strong Python and SQL; C++, C#, or MATLAB a plus. Databases: PostgreSQL, SQL Server, Oracle, Snowflake, Iceberg, TimescaleDB. Data Platform Capabilities ...

What the role entails: Some of the main duties of the Data Engineer will include: Develop high-performance data pipelines using Python (Pandas) or Spark within Palantir Foundry, ensuring seamless data transformation and integration to support analytics, reporting, and machine learning use cases across the enterprise. Design and implement ...

Oracle). Comprehensive knowledge of European and international gas and power markets, covering physical and financial trading, forward/futures/options, basis risk, spark and dark spreads, gas balancing, power scheduling, nominations, LNG and cross-commodity optimisation. Proven track record of defining and delivering enterprise-level architecture ...

Oracle). Comprehensive knowledge of European and international gas and power markets, covering physical and financial trading, forward/futures/options, basis risk, spark and dark spreads, gas balancing, power scheduling, nominations, LNG and cross-commodity optimisation. Proven track record of defining and delivering enterprise-level architecture ...

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 ...

experience with the SQL Server platform and T-SQL querying. Familiarity with cloud data platforms (e.g., AWS, Azure) and big data technologies (e.g., Kafka, Spark, Databricks, Snowflake). Expert-level knowledge of building ETL processes in Python. Expert-level knowledge of performance tuning and optimization in a Python/ ...

auction systems Excellent communication skills, able to explain complex technical systems to commercial, operations and senior leadership teams. Experience with Google Cloud, Docker, Kafka, Spark, Airflow, ElasticSearch, ClickHouse or similar production infrastructure Experience owning product roadmaps, release governance or cross-functional delivery across distributed teams and time zones. What ...

source models or integrating with managed foundation model platforms. Hands-on experience building data pipelines and model workflows using tools such as Python, SQL, Spark or similar data processing technologies. Experience deploying and operating AI systems in cloud environments using containerisation, managed ML services or serverless architectures. Understanding ...

ownership.Experience designing and enforcing data contracts and quality SLAs in distributed data ecosystems.Proficiency in Python, Java, or Scala, and experience building pipelines with Databricks, Spark, or Kafka.Strong understanding of data governance principles, privacy regulations (GDPR, CCPA), and secure data handling practices.Familiarity with metadata management and data catalog tools (e.g.DataHub ...

including data modelling, DAX and semantic model design Hands-on experience with Microsoft Fabric, particularly lakehouse architecture, notebooks and data pipelines Strong understanding of Apache Spark/PySpark and large-scale data processing Experience designing and operating modern data platforms Experience developing or enabling AI and machine learning ...

teams to drive outcomes Core skills (indicative) Production pipeline design and deployment experience Strong engineering capability with Python, SQL, plus big data tooling (e.g., Spark, and Java/Scala where relevant AWS, Azure, GCP Working pattern Hybrid working, with the team on client site or in the office ...

teams to drive outcomes Core skills (indicative) Production pipeline design and deployment experience Strong engineering capability with Python, SQL, plus big data tooling (e.g., Spark, and Java/Scala where relevant AWS, Azure, GCP Working pattern Hybrid working, with the team on client site or in the office ...

/CD) practices Useful skills: Working knowledge of using GEN AI tools for coding Experience with Python/Scala or big data frameworks (e.g. spark) or Batch Processing. Working knowledge or certifications relevant to public cloud, preferably AWS. Experience with any of streaming, messaging, event bus technologies while building ...

scalable data analytical solutions in a large-scale business environment Experience in deep analytic focused work leveraging Distributed File System ecosystem tools: Linux, Python, Spark, Hive; and modern data platforms and tools (e.g. Databricks, NoSQL stores) and AI/ML frameworks (e.g. NLP). LLM integration patterns, RAG pipelines ...

will look like Understand Ubuntu, Linux, networking and services in real‐world environments Architect cloud infrastructure solutions such as Kubernetes, Kubeflow, OpenStack, Ceph and Spark on‐premises or in public clouds (AWS, Azure, Google Cloud) Architect and integrate popular open‐source software such as PostgreSQL, MongoDB, Kafka, Cassandra ...