76 to 100 of 167 PySpark Jobs in England

testing, including ETL, data warehouse, and reporting validation. Strong hands-on knowledge of AWS data tools (Glue, Redshift, Athena, EMR, Lambda). Confident with Power BI, SQL, Python/PySpark, and QA automation tools. Solid grasp of data governance, GDPR, and data quality standards. Background in Agile delivery and experience leading or mentoring QA teams. Strong analytical mindset with More ❯

personalized digital interactions.Some Technologies We Work With:Python primarily, with bits and pieces of typescript and scalaGCP, AWS, Azure - in this order of relevanceGitHub, Docker, GitHub Actions, Terraform, KubernetesPandas, PySpark and SparkVertex AI, Azure OpenAI for LLMs Job Responsibilities Lead the execution of projects in a high-performing data science team, fostering professional growth and creating an inclusive and More ❯

and machine learning use cases. Support the migration of legacy reporting tools into Databricks and modern BI solutions. Key Skills & Experience Essential: Strong hands-on experience with Databricks (SQL, PySpark, Delta Lake). Solid knowledge of BI and data visualisation tools (e.g., Power BI, Tableau, Qlik). Strong SQL and data modelling skills. Experience working with large, complex financial More ❯

and machine learning use cases. Support the migration of legacy reporting tools into Databricks and modern BI solutions. Key Skills & Experience Essential: Strong hands-on experience with Databricks (SQL, PySpark, Delta Lake). Solid knowledge of BI and data visualisation tools (e.g., Power BI, Tableau, Qlik). Strong SQL and data modelling skills. Experience working with large, complex financial More ❯

and machine learning use cases. Support the migration of legacy reporting tools into Databricks and modern BI solutions. Key Skills & Experience Essential: Strong hands-on experience with Databricks (SQL, PySpark, Delta Lake). Solid knowledge of BI and data visualisation tools (e.g., Power BI, Tableau, Qlik). Strong SQL and data modelling skills. Experience working with large, complex financial More ❯

and machine learning use cases. Support the migration of legacy reporting tools into Databricks and modern BI solutions. Key Skills & Experience Essential: Strong hands-on experience with Databricks (SQL, PySpark, Delta Lake). Solid knowledge of BI and data visualisation tools (e.g., Power BI, Tableau, Qlik). Strong SQL and data modelling skills. Experience working with large, complex financial More ❯

and machine learning use cases. Support the migration of legacy reporting tools into Databricks and modern BI solutions. Key Skills & Experience Essential: Strong hands-on experience with Databricks (SQL, PySpark, Delta Lake). Solid knowledge of BI and data visualisation tools (e.g., Power BI, Tableau, Qlik). Strong SQL and data modelling skills. Experience working with large, complex financial More ❯

Experience in a Data Engineer/Data Engineering role Large and complex datasets Azure, Azure Databricks Microsoft SQL Server Lakehouse, Delta Lake Data Warehousing ETL Database Design Python/PySpark Azure Blob Storage Azure Data Factory Desirable: Exposure ML/Machine Learning/AI/Artificial Intelligence More ❯

and influence decisions. Strong understanding of data models and analytics; exposure to predictive modelling and machine learning is a plus. Proficient in SQL and Python, with bonus points for PySpark, SparkSQL, and Git. Skilled in data visualisation with tools such as Tableau or Power BI. Confident writing efficient code and troubleshooting sophisticated queries. Clear and adaptable communicator, able to More ❯

C#, C++, Rust, Java, etc.). Strong background in Azure cloud application development, including security, observability, storage, and database resources. Solid understanding of data engineering tools and technologies (Databricks, PySpark, Lakehouses, Kafka). Advanced mathematics and quantitative analysis skills, ideally with hands-on experience in probabilistic modeling and the valuation of financial derivatives. Domain expertise in derivatives within energy More ❯

C#, C++, Rust, Java, etc.). Strong background in Azure cloud application development, including security, observability, storage, and database resources. Solid understanding of data engineering tools and technologies (Databricks, PySpark, Lakehouses, Kafka). Advanced mathematics and quantitative analysis skills, ideally with hands-on experience in probabilistic modeling and the valuation of financial derivatives. Domain expertise in derivatives within energy More ❯

Supportingbestpracticesin datagovernance,securityandarchitecture . Buildingandoptimisingpipelinesacrosscloudandon-premiseenvironments. Collaboratingwithstakeholders,engineers,andanalyststodeliverintegratedsolutions. Ensuringconsistencyacrosstransactionalandanalyticaldatasystems. Contributingtothedevelopmentof datalakes,datawarehouses,anddistributedstorageenvironments . Mentoringjuniorengineers,embeddingbestpracticeacrosstheteam. Whatwerelookingfor 5+yearsexperiencein DataEngineering ,withstrongexpertisein Azuredataservicesand/orMicrosoftFabric . Proventrackrecorddesigningscalableplatformsandmanaginglargecloud-basedecosystems. Proficiencyin Python,PySpark,SQL,NoSQL andframeworkssuchas Databricks . Solidexperiencewith ETL/ELTdesign,orchestrationandoptimisation . Knowledgeof datagovernance,privacyregulations,andsecuritybestpractices . Strongexperienceintegratingrelational,NoSQL,andstreamingdatasources. CompetenceinCI/CDpipelinesandGit-basedworkflows. Experiencewithmodernarchitecturesincluding datamesh,event-drivenprocessing,andstreamingplatforms(Kafka More ❯

Deliver end-to-end BI solutions using Azure Synapse, ADF, and Power BI (Datasets & Reports) Design and implement scalable data models and architectures Develop robust pipelines using SQL, Python (PySpark), and ideally other OOP languages Manage CI/CD processes using Git and modern deployment tools Debug, monitor, and optimize BI solutions across Microsoft's stack, including legacy tools More ❯

Excellent understanding of AWS Data Platforms, with services such as AWS Glue, S3, Lambda, Redshift, etc. Good understanding of management principles for data pipelines and ETL Good Python and PySpark Use of SQL Data platforms If you have experience migrating from an on-premise to cloud based solution this would be a bonus Excellent cross-team collaboration skills Ability More ❯

/executing tests Requirements Strong experience as a Data Engineer (migrating legacy systems onto AWS, building data pipelines) Strong Python experience Tech stack experience required: AWS Glue, Redshift, Lambda, PySpark, Airflow SSIS or SAS experience (Desirable) Benefits Salary up to £57,500 + up to 20% bonus Hybrid working: 1 to 2 days a week in the office More ❯

also identifying transformational opportunities for sales productivity. 🔑 What You’ll Bring Must-Have Skills 5+ years in Sales Ops/Rev Ops roles Proficient in SQL and Python (Pandas, PySpark) Strong experience with cloud data platforms (Databricks, Snowflake, GCP) Background in building ETL/ELT solutions and data modelling Advanced Excel/Power BI/VBA skills 2+ years More ❯

also identifying transformational opportunities for sales productivity. 🔑 What You’ll Bring Must-Have Skills 5+ years in Sales Ops/Rev Ops roles Proficient in SQL and Python (Pandas, PySpark) Strong experience with cloud data platforms (Databricks, Snowflake, GCP) Background in building ETL/ELT solutions and data modelling Advanced Excel/Power BI/VBA skills 2+ years More ❯

AWS/Azure - moving towards Azure). Collaborate with stakeholders and technical teams to deliver solutions that support business growth. Skills & Experience Required: Strong hands-on experience in Python, PySpark, SQL, Jupyter . Experience in Machine Learning engineering or data-focused development. Exposure to working in cloud platforms (AWS/Azure) . Ability to collaborate effectively with senior engineers More ❯

results. What we're looking for: Proven experience in Data Architecture and data modelling. Strong skills in Microsoft Azure tools (Fabric, OneLake, Data Factory). Confident with Python/PySpark and relational databases. Hands-on ETL/ELT experience. A problem-solver with a positive, can-do attitude. Bonus points if you bring: Tableau, Power BI, SSAS, SSIS or More ❯

results. What we're looking for: Proven experience in Data Architecture and data modelling. Strong skills in Microsoft Azure tools (Fabric, OneLake, Data Factory). Confident with Python/PySpark and relational databases. Hands-on ETL/ELT experience. A problem-solver with a positive, can-do attitude. Bonus points if you bring: Tableau, Power BI, SSAS, SSIS or More ❯

within a cross-functional environment. Experience in line management or team leadership, with a track record of developing and supporting engineers. AWS (Lambda, Glue, ECS, S3, etc.) Python and PySpark (data pipelines, APIs, automation) TypeScript and React (frontend development) Excellent communication and stakeholder management skills. Demonstrated expertise in technical design and architecture of distributed systems. Familiarity with fraud detection More ❯

within a cross-functional environment. Experience in line management or team leadership, with a track record of developing and supporting engineers. AWS?(Lambda, Glue, ECS, S3, etc.) Python and PySpark?(data pipelines, APIs, automation) TypeScript and React?(frontend development) Excellent communication and stakeholder management skills. Demonstrated expertise in technical design and architecture of distributed systems. Familiarity with fraud detection More ❯

roles.? Ability to manage multiple projects and priorities in a fast-paced environment.? Experience with SSRS/SSAS (Tabular with DAX & OLAP with MDX)/SSIS? Experience with Databricks, Pyspark, and other data sciences tools Experience of using Azure DevOps/Git? Microsoft Certified on Data (e.g. Fabric) This is a client-facing role, so the following are essential More ❯

understanding of AI/ML/DL and Statistics, as well as coding proficiency using related open source libraries and frameworks. Significant proficiency in SQL and languages like Python, PySpark and/or Scala. Can lead, work independently as well as play a key role in a team. Good communication and interpersonal skills for working in a multicultural work More ❯

the delivery of one of the organisation's key strategic initiatives. Experience required: AWS Data/ML Engineering & ML Ops (ECS, Sagemaker) CI/CD pipelines (GitLab, Jenkins) Python, PySpark & Big Data ecosystems AI/ML lifecycle, deployment & monitoring MLOps tooling (MLflow, Airflow, Docker, Kubernetes) Front-end exposure (HTML, Flask, Streamlit) RESTful APIs & backend integration If this ML Engineer More ❯