1 to 25 of 131 Remote PySpark Jobs in the UK excluding London

/CD) automation, rigorous code reviews, documentation as communication. Preferred Qualifications Familiar with data manipulation and experience with Python libraries like Flask, FastAPI, Pandas, PySpark, PyTorch, to name a few. Proficiency in statistics and/or machine learning libraries like NumPy, matplotlib, seaborn, scikit-learn, etc. Experience in building More ❯

various departments to gather requirements and ensure data solutions reflect real business needs. Key Experience Required: Deep expertise in SQL, Python, and Spark (particularly PySpark) for building and testing end-to-end pipelines in that process both structured and semi-structured datasets. Experience mentoring peers and supporting team growth More ❯

various departments to gather requirements and ensure data solutions reflect real business needs. Key Experience Required: Deep expertise in SQL, Python, and Spark (particularly PySpark) for building and testing end-to-end pipelines in that process both structured and semi-structured datasets. Experience mentoring peers and supporting team growth More ❯

working in cloud-native environments (AWS preferred) Strong proficiency with Python and SQL Extensive hands-on experience in AWS data engineering technologies, including Glue, PySpark, Athena, Iceberg, Databricks, Lake Formation, and other standard data engineering tools. Familiarity with DevOps practices and infrastructure-as-code (e.g., Terraform, CloudFormation) Solid understanding More ❯

experience as a Senior Data Engineer, with some experience mentoring others Excellent Python and SQL skills, with hands-on experience building pipelines in Spark (PySpark preferred) Experience with cloud platforms (AWS/Azure) Solid understanding of data architecture, modelling, and ETL/ELT pipelines Experience using tools like Databricks More ❯

Knowledge, Skills and Experience: Essentia l Strong expertise in Databricks and Apache Spark for data engineering and analytics. Proficient in SQL and Python/PySpark for data transformation and analysis. Experience in data lakehouse development and Delta Lake optimisation. Experience with ETL/ELT processes for integrating diverse data More ❯

encryption best practices. Nice-to-Have Skills Exposure to AWS Redshift, Glue, or Snowflake. Familiarity with BigQuery and Google Analytics APIs. Proficiency in Python, PySpark, or dbt for data transformations. Background in insurance, especially in pricing analytics or actuarial data. Click Apply More ❯

a highly numerate subject is essential At least 2 years of Python development experience, including scientific computing and data science libraries (NumPy, pandas, SciPy, PySpark) Strong understanding of object-oriented design principles for usability and maintainability Experience with Git in a version-controlled environment Knowledge of parallel computing techniques More ❯

a highly numerate subject is essential At least 2 years of Python development experience, including scientific computing and data science libraries (NumPy, pandas, SciPy, PySpark) Strong understanding of object-oriented design principles for usability and maintainability Experience with Git in a version-controlled environment Knowledge of parallel computing techniques More ❯

A A B grades at A-level You have commercial Data Engineering experience working with technologies such as SQL, Apache Spark and Python including PySpark and Pandas You have a good understanding of modern data engineering best practices Ideally you will also have experience with Azure and Data Bricks More ❯

Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure/AWS Data Engineering certifications Databricks certifications What's in it for More ❯

Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure/AWS Data Engineering certifications Databricks certifications What's in it for More ❯

Strong experience designing and delivering data solutions in Databricks Proficient with SQL and Python Experience using Big Data technologies such as Apache Spark or PySpark Great communication skills, effectively participating with Senior Stakeholders Nice to haves: Azure/AWS Data Engineering certifications Databricks certifications What's in it for More ❯

initiatives Key Requirements of the Database Engineer: Proven experience with Databricks, Azure Data Lake, and Delta Live Tables Strong programming in Python and Spark (PySpark or Scala) Solid knowledge of data modelling, warehousing, and integration concepts Comfortable working in Agile teams, with CI/CD and Azure DevOps experience More ❯

initiatives Key Requirements of the Database Engineer: Proven experience with Databricks, Azure Data Lake, and Delta Live Tables Strong programming in Python and Spark (PySpark or Scala) Solid knowledge of data modelling, warehousing, and integration concepts Comfortable working in Agile teams, with CI/CD and Azure DevOps experience More ❯

similar tools is valuable (Collibra, Informatica Data Quality/MDM/Axon etc.) Data Architecture experience is a bonus Python, Scala, Databricks Spark and Pyspark with Data Engineering skills Ownership and ability to drive implementation/solution design More ❯

cloud-based architectures on AWS, Azure, or GCP A strong background in Databricks for building enterprise data warehouses with strong knowledge of SQL and Pyspark A deep understanding of data modelling and advanced pipeline development Knowledge and understanding of best practice CI/CD approaches utilising Git. Strategic Vision More ❯

Collaborate across technical and non-technical teams Troubleshoot issues and support wider team adoption of the platform What You’ll Bring: Proficiency in Python, PySpark, Spark SQL or Java Experience with cloud tools (Lambda, S3, EKS, IAM) Knowledge of Docker, Terraform, GitHub Actions Understanding of data quality frameworks Strong More ❯

data for reporting and analytics Ensuring data quality and integrity through validation and cleansing techniques What We're Looking For: Strong proficiency in SQL , Pyspark and Python Hands-on experience with Microsoft Fabric Previous experience in a collaborative, data-driven team Bonus Points For: Experience working with D365 F More ❯

in programming languages and data structures such as SAS, Python, R, SQL is key. With Python background, particularly familiarity with pandas/polars/pyspark, pytest; understanding of OOP principles; git version control; knowledge of the following frameworks a plus: pydantic, pandera, sphinx Additionally, experience in any or all More ❯

Azure-based platforms (Synapse, Data Factory, Databricks) Familiarity with data regulations (GDPR, FCA) and SMCR environments Bonus points for experience with Python, R, or PySpark Why You Should Apply: Executive-level visibility and the chance to lead a high-impact transformation Full budget ownership with freedom to shape systems More ❯

AI Platforms: Google Cloud Platform, Amazon Web Services, Microsoft Azure, Databricks. Experience in one or more of the listed Languages or Packages: Python, R, Pyspark, Scala, PowerBI, Tableau. Proven experience in successfully delivering multiple complex data rich workstreams in parallel to supporting wider strategic ambitions and supporting others in More ❯

ground running in Databricks and ideally have knowledge of Apache Spark. Naturally you'll have sound SQL exposure and AWS from a Cloud perspective. Pyspark would be hugely advantageous to this position too. The platform integrates Power BI so it would be fab if you could present complex reports More ❯

effectiveness, including Azure DevOps. Considerable experience designing and building operationally efficient pipelines, utilising core Azure components, such as Azure Data Factory, Azure Databricks and Pyspark etc. Proven experience in modelling data through a medallion-based architecture, with curated dimensional models in the gold layer built for analytical use. Strong More ❯

Knowledge of Data Warehouse/Data Lake architectures and technologies. Strong working knowledge of a language for data analysis and scripting, such as Python, Pyspark, R, Java, or Scala. Experience with any of the following would be desirable but not essential; Microsoft's Fabric data platform, Experience with ADF More ❯