15 of 15 PySpark Jobs in Berkshire

including Azure DevOps or GitHub Considerable experience designing and building operationally efficient pipelines, utilising core Cloud components, such as Azure Data Factory, Big Query, AirFlow, Google Cloud Composer 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 understanding and or use of More ❯

are an experienced Data Engineer within financial services environments You have expertise with GCP including BigQuery, Pub/Sub, Cloud Composer and IAM You have strong Python, SQL and PySpark skills You have experience with real-time data streaming using Kafka or Spark You have a good knowledge of Data Lakes, Data Warehousing, Data Modelling You're familiar with More ❯

including Azure DevOps or GitHub Considerable experience designing and building operationally efficient pipelines, utilising core Cloud components, such as Azure Data Factory, Big Query, AirFlow, Google Cloud Composer 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 understanding and or use of 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 ❯

having delivered in Microsoft Azure 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 Data Engineering certifications Databricks certifications What's in it for you: 📍Location: London (Hybrid) 💻Remote working: Occasional More ❯

leadership and upskilling responsibilities. Key Responsibilities Build and maintain Databricks Delta Live Tables (DLT) pipelines across Bronze → Silver → Gold layers, ensuring quality, scalability, and reliability. Develop and optimise Spark (PySpark) jobs for large-scale distributed processing. Design and implement streaming data pipelines with Kafka/MSK, applying best practices for late event handling and throughput. Use Terraform and CI More ❯

improve AI models over time. REQUIREMENTS 2 years of proven experience in data engineering for ML/AI, with strong proficiency in Python, SQL, and distributed data processing (e.g., PySpark). Hands-on experience with cloud data platforms (GCP, AWS, or Azure), orchestration frameworks (e.g., Airflow), and ELT/ETL tools. Familiarity with 2D and 3D data formats (e.g. More ❯

data platforms, and integrations, while ensuring solutions meet regulatory standards and align with architectural best practices. Key Responsibilities: Build and optimise scalable data pipelines using Databricks and Apache Spark (PySpark). Ensure performance, scalability, and compliance (GxP and other standards). Collaborate on requirements, design, and backlog refinement. Promote engineering best practices including CI/CD, code reviews, and More ❯

data-driven culture all within a collaborative environment that values innovation and ownership. Tech you’ll be working with: Azure Data Lake Azure Synapse Databricks Data Factory Python, SQL, PySpark Terraform, GitHub Actions, CI/CD pipelines You’ll thrive here if you: Have strong experience building and leading Azure-based data platforms Enjoy mentoring and guiding other engineers More ❯

and development plan beyond generic certifications. Provide a Rough Order of Magnitude (ROM) cost for implementing the proposed roadmap. Essential Deep expertise in the Databricks Lakehouse Platform, including Python, PySpark, and advanced SQL. Strong practical knowledge of Microsoft Fabric. Proven experience in senior, client-facing roles with a consultancy mindset. Background in technical coaching, mentorship, or skills assessment. Excellent More ❯

Studio and data transformation logic Azure Fabric, Azure Data Factory, Synapse, Data Lakes and Lakehouse/Warehouse technologies ETL/ELT orchestration for structured and unstructured data Proficiency in: PySpark, T-SQL, Notebooks and advanced data manipulation Performance monitoring and orchestration of Fabric solutions Power BI semantic models and Fabric data modelling DevOps deployment using ARM/Bicep templates More ❯

Google Cloud Platform (GCP) Strong experience designing and delivering data solutions using BigQuery Proficient in SQL and Python Experience working with Big Data technologies such as Apache Spark or PySpark Excellent communication skills, with the ability to engage effectively with senior stakeholders Nice to haves: GCP Data Engineering certifications BigQuery or other GCP tool certifications What’s in it More ❯

and validate data models and outputs Set up monitoring and ensure data health for outputs What we are looking for Proficiency in Python, with experience in Apache Spark and PySpark Previous experience with data analytics softwares Ability to scope new integrations and translate user requirements into technical specifications What’s in it for you? Base salary of More ❯

analytics efforts. Required Skills & Experience: 4–5 years of commercial experience in data science , preferably in eCommerce or marketing analytics. Strong hands-on experience with Databricks, SQL, Python, and PySpark ; knowledge of R and dashboarding tools is a plus. Proven experience with causal inference, MMM modelling, and experimentation . Strong analytical and problem-solving skills with the ability to More ❯

platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark or Scala) and other relevant technologies. Develop and maintain data processing logic for cleaning, enriching, and aggregating data. Ensure data consistency and accuracy throughout the data lifecycle. Azure Databricks … practices. Essential Skills & Experience: 10+ years of experience in data engineering, with at least 3+ years of hands-on experience with Azure Databricks. Strong proficiency in Python and Spark (PySpark) or Scala. Deep understanding of data warehousing principles, data modelling techniques, and data integration patterns. Extensive experience with Azure data services, including Azure Data Factory, Azure Blob Storage, and More ❯