1 to 25 of 38 Parquet Jobs in the UK

tools (QuickSight, Power BI, Tableau, Looker, etc.) Interest or experience in building internal data communities or enablement programs Working with diverse data sources (APIs, CRMs, SFTP, databases) and formats (Parquet, JSON, XML, CSV) Exposure to machine learning models or AI agents Why Join Us Help shape the future of data in an organization that treats data as a product More ❯

data models. Expertise in implementing Data Lake/Big Data projects in Cloud MS Azure and/or On-premise platforms. Experience with designing and building lakehouse architectures in Parquet/Delta and Synapse Serverless or Databricks SQL. Working experience with DevOps frameworks and a strong understanding of Software Development Lifecycle. Experience in performing root cause analysis on data More ❯

Data modelling (building optimised and efficient data marts and warehouses in the cloud) Work with Infrastructure as code (Terraform) and containerising applications (Docker) Work with AWS, S3, SQS, Iceberg, Parquet, Glue and EMR for our Data Lake Experience developing CI/CD pipelines More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy More ❯

services, especially Glue, Athena, Lambda, and S3 . Proficient in Python (ideally PySpark) and modular SQL for transformations and orchestration. Solid grasp of data modeling (partitioning, file formats like Parquet, etc.). Comfort with CI/CD, version control, and infrastructure-as-code tools. If this sends like you then send your CV More ❯

real-time streaming applications preferably with experience in Kafka Real-time messaging or Azure Stream Analytics/Event Hub. Spark processing and performance tuning. File formats partitioning for e.g. Parquet, JSON, XML, CSV. Azure DevOps, GitHub actions. Hands-on experience in at least one of Python with knowledge of the others. Experience in Data modeling. Experience of synchronous and More ❯

Expert knowledge of the Microsoft Fabric Analytics Platform (Azure SQL, Synapse, PowerBI). • Proficient in Python for data engineering tasks, including data ingestion from APIs, creation and management of Parquet files, and execution of ML models. • Strong SQL skills, enabling support for Data Analysts with efficient and performant queries. • Skilled in optimizing data ingestion and query performance for MSSQL More ❯

AWS serverless services and enables powerful querying and analytics through Amazon Athena. In this role, you'll work on a system that combines streaming ingestion (Firehose), data lake technologies (Parquet, Apache Iceberg), scalable storage (S3), event-driven processing (Lambda, EventBridge), fast access databases (DynamoDB), and robust APIs (Spring Boot microservices on EC2). Your role will involve designing, implementing … processing pipeline and platform services. Key Responsibilities: Design, build, and maintain serverless data processing pipelines using AWS Lambda, Firehose, S3, and Athena. Optimize data storage and querying performance using Parquet and Iceberg formats. Manage and scale event-driven workflows using EventBridge and Lambda. Work with DynamoDB for fast, scalable key-value storage. Develop and maintain Java Spring Boot microservices … Java backend development experience. 3+ years of Python development. Strong hands-on experience with AWS services: Lambda, S3, K8S. Deep understanding of data lake architectures and formats such as Parquet and Iceberg. Proficiency in Spring Boot and working experience with microservices. Experience with high-scale, event-driven systems and serverless patterns. Nice to Have: Solid understanding of distributed systems More ❯

hands-on AWS experience – S3, Redshift, Glue essential. Proven experience building ETL/ELT pipelines in cloud environments. Proficient in working with structured/unstructured data (JSON, XML, CSV, Parquet). Skilled in working with relational databases and data lake architectures. Experienced with Matillion and modern data visualisation tools (QuickSight, Tableau, Looker, etc.). Strong scripting and Linux/ More ❯

hands-on AWS experience – S3, Redshift, Glue essential. Proven experience building ETL/ELT pipelines in cloud environments. Proficient in working with structured/unstructured data (JSON, XML, CSV, Parquet). Skilled in working with relational databases and data lake architectures. Experienced with Matillion and modern data visualisation tools (QuickSight, Tableau, Looker, etc.). Strong scripting and Linux/ More ❯

and Matillion Translate client requirements into scalable and secure data architectures Drive infrastructure-as-code and CI/CD deployment practices Process structured and semi-structured data (JSON, XML, Parquet, CSV) Maintain metadata, build data dictionaries, and ensure governance is embedded by design Work across industries in fast-paced, high-value engagements This Principal Data Engineer will bring: Extensive More ❯

and Matillion Translate client requirements into scalable and secure data architectures Drive infrastructure-as-code and CI/CD deployment practices Process structured and semi-structured data (JSON, XML, Parquet, CSV) Maintain metadata, build data dictionaries, and ensure governance is embedded by design Work across industries in fast-paced, high-value engagements This Principal Data Engineer will bring: Extensive More ❯

we do Passion for data and experience working within a data driven organization Hands-on experience with architecting, implementing, and performance tuning of: Data Lake technologies (e.g. Delta Lake, Parquet, Spark, Databricks) API & Microservices Message queues, streaming technologies, and event driven architecture NoSQL databases and query languages Data domain and event data models Data Modelling Logging and monitoring Container More ❯

data warehousing (e.g. Hadoop, Spark, Redshift, Snowflake, GCP BigQuery) Expertise in building data architectures that support batch and streaming paradigms Experience with standards such as JSON, XML, YAML, Avro, Parquet Strong communication skills Open to learning new technologies, methodologies, and skills As the successful Data Engineering Manager you will be responsible for: Building and maintaining data pipelines Identifying and More ❯

scalable data pipelines using PySpark 3/4 and Python 3. * Contribute to the creation of a unified data lake following medallion architecture principles. * Leverage Databricks and Delta Lake (Parquet format) for efficient, reliable data processing. * Apply BDD testing practices using Python Behave and ensure code quality with Python Coverage. * Collaborate with cross-functional teams and participate in Agile More ❯

scalable data pipelines using PySpark 3/4 and Python 3. * Contribute to the creation of a unified data lake following medallion architecture principles. * Leverage Databricks and Delta Lake (Parquet format) for efficient, reliable data processing. * Apply BDD testing practices using Python Behave and ensure code quality with Python Coverage. * Collaborate with cross-functional teams and participate in Agile More ❯

management systems . Analyze and cleanse data using a range of tools and techniques. Manage and process structured and semi-structured data formats such as JSON, XML, CSV, and Parquet . Operate effectively in Linux and cloud-based environments . Support CI/CD processes and adopt infrastructure-as-code principles. Contribute to a collaborative, knowledge-sharing team culture. More ❯

management systems . Analyze and cleanse data using a range of tools and techniques. Manage and process structured and semi-structured data formats such as JSON, XML, CSV, and Parquet . Operate effectively in Linux and cloud-based environments . Support CI/CD processes and adopt infrastructure-as-code principles. Contribute to a collaborative, knowledge-sharing team culture. More ❯

Experience with alternative data technologies (e.g. duckdb, polars, daft). Familiarity with eventing technologies (Event Hubs, Kafka etc ). Deep understanding of file formats and their behaviour such as parquet, delta and iceberg. What we offer We want to give you a great work environment; contribute back to both your personal and professional development; and give you great benefits More ❯

ML workflows is a plus. Hands-on experience with multi-terabyte scale data processing. Familiarity with AWS; Kubernetes experience is a bonus. Knowledge of data lake technologies such as Parquet, Iceberg, AWS Glue etc. Strong Python software engineering skills. Pragmatic mindset - able to evaluate tradeoffs find solutions that empower ML researchers to move quickly. Background in bioinformatics or chemistry More ❯

globally distributed environment. Ideal, But Not Required Experience with Vega, Observable Plot, ggplot or another grammar-of-graphics library. Experience in Python, FastAPI Expertise in data engineering topics, SQL, parquet Experience with AWS services and serverless architectures. What we offer Work with colleagues that lift you up, challenge you, celebrate you and help you grow. We come from many More ❯

Cloud and big data technologies (e.g. Spark/Databricks/Delta Lake/BigQuery). Familiarity with eventing technologies (e.g. Event Hubs/Kafka) and file formats such as Parquet/Delta/Iceberg. Want to learn more? Get in touch for an informal chat. More ❯

options such as ECS, EKS, and Lambda IAM - Experience handling IAM resource permissions Networking - fundamental understanding of VPC, subnet routing and gateways Storage - strong understanding of S3, EBS and Parquet Databases - RDS, DynamoDB Experience doing cost estimation in Cost Explorer and planning efficiency changes Terraform and containerisation experience Understanding of a broad range of protocols like HTTP, TCP, gRPC More ❯

design workshops including estimating, scoping and delivering customer proposals aligned with Analytics Solutions - Experience with one or more relevant tools (Sqoop, Flume, Kafka, Oozie, Hue, Zookeeper, HCatalog, Solr, Avro, Parquet, Iceberg, Hudi) - Experience developing software and data engineering code in one or more programming languages (Java, Python, PySpark, Node, etc) - AWS and other Data and AI aligned Certifications PREFERRED More ❯

with Azure Integration Services (e.g., Logic Apps, ADF, Service Bus, Functions) Comfortable working with Git, Azure DevOps, and unit testing practices Knowledge of common data formats: CSV, JSON, XML, Parquet Ability to lead integration designs with minimal rework required Preferred Qualifications Certification in SSIS or relevant Microsoft technologies Proven track record of delivering robust integration solutions Key Skills & Traits More ❯

with Azure Integration Services (e.g., Logic Apps, ADF, Service Bus, Functions) Comfortable working with Git , Azure DevOps , and unit testing practices Knowledge of common data formats: CSV, JSON, XML, Parquet Ability to lead integration designs with minimal rework required 🧾 Preferred Qualifications 🎓 Certification in SSIS or relevant Microsoft technologies 💡 Proven track record of delivering robust integration solutions 🧠 Key Skills & Traits More ❯