76 to 100 of 372 Apache Spark Jobs in England

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 ...

Python and SQL; APIs; test automation; data structures; distributed processing; Git; CI/CD; containers; infrastructure awareness; production debugging and performance optimization. Data engineering: Spark or Databricks, Kafka or equivalent streaming, ETL/ELT, batch and real-time pipelines, data contracts, lineage, cataloguing, quality rules, and scalable cloud storage. ...

Robust knowledge of data engineering, including data modelling, ETL/ELT, pipeline orchestration, testing, and data quality management.* Hands-on experience with Databricks and Apache Spark to build and operate scalable data pipelines and analytics or AI workflows.* Proven proficiency in applied AI, demonstrated through delivered solutions using ...

Robust knowledge of data engineering, including data modelling, ETL/ELT, pipeline orchestration, testing, and data quality management. Hands-on experience with Databricks and Apache Spark to build and operate scalable data pipelines and analytics or AI workflows. Proven proficiency in applied AI, demonstrated through delivered solutions using ...

Knowledge of data modelling, data warehousing and Lakehouse architectures . Experience with data quality, governance and CI/CD pipelines . Exposure to Kafka, Spark Streaming or real-time data processing would be advantageous. Requirements: Ideally 7+ years of commercial Data Engineering experience. Strong hands-on technical background ...

Lake Storage. Advanced SQL development and performance tuning skills, including experience with Azure SQL Database and SQL Server. Proficiency in Python, PySpark, Scala and Spark for data processing and distributed computing. Understanding of data warehousing concepts, dimensional modelling and ETL/ELT frameworks. Knowledge of data quality, data governance ...

large-scale ETL development. Proficiency in SQL and programming languages such as Python, Java, or Scala. Hands‐on experience with big data frameworks (e.g., Spark, Hadoop, Flink) and cloud platforms (AWS, GCP, or Azure). Familiarity with data warehouse technologies (e.g., Snowflake, Redshift, BigQuery) and workflow orchestration tools (e.g. ...

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 ...

with the modern data stack, building data ingestion pipelines and working with ETL and orchestration tools (e.g., Airflow, Luigi, Argo, dbt), big data technologies (Spark, Kafka, Parquet), and web frameworks for model serving (e.g. Flask or FastAPI). Data Science: Familiarity or experience with classical NLP techniques (BERT, topic ...

concepts and how they can be applied to improve quality processes and drive continuous improvement. Exposure to data engineering and analytics tools (e.g., Databricks, Spark, Airflow or dbt). Awareness of cloud platforms (AWS, Azure or GCP). Experience with Git, CI/CD or Agile practices (from university ...

including lakehouses, data warehousing, ETL/ELT pipelines, orchestration, and dimensional data modelling. Hands‐on experience with modern data technologies such as dbt, Databricks, Spark, SQL, and Python. Understanding of semantic layers, data governance, and the foundations required for trustworthy AI‐powered analytics. Strong technical foundation, with experience designing ...

Strong hands-on experience with Azure Cosmos DB, including SQL API and Mongo API. Excellent knowledge of Cosmos DB Change Data Feed (CDF) and Spark integration. Strong PySpark and Apache Spark distributed computing experience. Experience with Cosmos DB SDKs, including .NET, Java, Python or Node.js. Expertise ...

BigQuery, Dataflow, Dataproc, Cloud Composer (Airflow), Pub/Sub, Cloud Storage, Bigtable, and Cloud SQL. Proficiency in Python and SQL, with experience in Spark or Apache Beam. Experience designing data warehouse and data lake architectures, including data modeling. Working experience with Terraform and CI/CD tooling such ...

analytics and AI/ML at enterprise scale.* Develop and optimise batch and streaming ETL/ELT pipelines using Azure Data Factory, PySpark, SQL, Apache Spark and Airflow, integrated with modern tooling like dbt and Git-based CI/CD.* Implement data cataloguing, lineage tracking and governance frameworks … data engineering, including designing and delivering data lake or lakehouse architectures in an enterprise cloud environment, ideally Microsoft Azure.* Hands-on expertise with Databricks, Spark, PySpark, SQL and core Azure Data Services (Data Lake Storage, Synapse Analytics, Data Factory).* Experience with data governance and cataloguing tools such ...

working with cloud‐native technologies, and applying robust software engineering practices. Key Responsibilities Design, develop, and optimise scalable, testable data pipelines using Python and Apache Spark. Implement batch workflows and ETL processes adhering to modern engineering standards. Develop Cloud-Based Workflows Orchestrate data workflows using AWS services such … Glue, EMR Serverless, Lambda, and S3. Contribute to the evolution of lakehouse architecture leveraging Apache Iceberg. Apply Software Engineering Best Practices Use version control, CI/CD pipelines, automated testing, and modular code principles. Participate in pair programming, code reviews, and architectural design sessions. Data Quality & Observability Build monitoring ...

product lifecycle. Hands‐on experience with large‐scale data processing and machine learning in production environments. Strong expertise in distributed computing frameworks such as Apache Spark or similar technologies. Solid understanding of machine learning workflows, including model development, deployment, and inference. Strong knowledge of modern data architectures, including ...

taking customers from EDW to the full capabilities of the Data Intelligence Platform. Demonstrated competence in the Lakehouse architecture including hands-on experience with Apache Spark, Python and SQL Excellent communication skills; both written and verbal Public Cloud Architecting: Hands-on experience designing and implementing big data architectures ...

gateways for AI applications Infrastructure as Code experience with Terraform, Ansible, or other IaC tools Experience building and managing data pipelines using tools like Apache Spark AI safety and governance experience with model evaluation, LLM judges, bias detection, and responsible AI practices Familiarity with statistical fundamentals and running ...

supporting or delivering migrations from Azure Synapse to Microsoft Fabric Advanced SQL: Strong SQL and T-SQL development, optimisation and troubleshooting skills. Python and Spark: Experience building data processing and transformation solutions using Python and Spark. Data engineering fundamentals: Strong understanding of ETL/ELT, data warehousing, dimensional modelling ...

data analytics, or data science, with the ability to work effectively with various data types and sources. Experience using big data technologies (e.g. Hadoop, Spark, Hive) and database management systems (e.g. SQL and NoSQL). Graph Database Expertise : Deep understanding of graph database concepts, data modeling, and query languages ...

culture where people feel safe to challenge ideas, learn, and grow. Nice to have Hands-on familiarity with the modern data stack — for example, Spark, Flink, Kafka, Debezium, Airflow, dbt, or similar — and with cloud platforms (AWS/GCP or equivalent) and modern DevOps practices. Experience leading teams that ...

services, a good understanding of cloud architecture, and proficiency with Terraform for provisioning and managing cloud infrastructure Experience building streaming data pipelines using Apache Flink, Apache Kafka, Spark Structured Streaming, or similar technologies Knowledge of modern data lakehouse architectures and ecosystem such as Kafka, Flink, Spark … with a SaaS or FinTech company Technologies we use: AWS Services: MSK, EC2, VPC, IAM, S3, SQS, Managed Flink, EKS Data Lakehouse: Kafka, Flink, Spark, Databricks, DBT, Debezium #J-18808-Ljbffr ...

cleansed, conformed business layers) while securely handling identifiable data. Scalable Data Processing: Develop, tune, and monitor large-scale batch processing pipelines using Azure Databricks (Spark-based processing) and PySpark. Orchestration & Workflow: Build automated data workflows using Microsoft Fabric Data Factory and Azure Data Factory to move data efficiently across … Microsoft Azure, with practical exposure to the Microsoft Fabric ecosystem (OneLake, Data Factory, Fabric Lakehouse). Big Data Processing: Deep technical expertise with Apache Spark/Azure Databricks for distributed compute, memory optimization, and Delta Lake formats. Data Engineering Languages: Advanced proficiency in SQL (T-SQL, SparkSQL ...

schemas for both structured and unstructured data with a snowflake environment Enhance cloud data capabilities, working with AWS S3, Azure Data Lake, and Apache Spark Collaborate with cross-functional teams to ensure data availability for advanced analytics and reporting Automate workflows, implement CI/CD pipelines, and maintain ...

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 ...