1 to 25 of 62 Remote PySpark Jobs

and data stores to support organizational requirements. Skills/Qualifications: 4+ years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. 3+ years hands-on experience with cloud services, especially Databricks, for building and managing scalable data pipelines 3+ years of proficiency in working with Snowflake or similar cloud More ❯

data engineering and reporting. Including storage, data pipelines to ingest and transform data, and querying & reporting of analytical data. You've worked with technologies such as Python, Spark, SQL, Pyspark, PowerBI etc. You're a problem-solver, pragmatically exploring options and finding effective solutions. An understanding of how to design and build well-structured, maintainable systems. Strong communication skills More ❯

Champion clean code, data lifecycle optimisation, and software engineering best practices What We're Looking For Proven hands-on experience with Databricks platform and orchestration Strong skills in Python, PySpark, and SQL, with knowledge of distributed data systems Expertise in developing full lifecycle data pipelines across ingestion, transformation, and serving layers Experience with data lakehouse architecture, schema design, and More ❯

like Retrieval-Augmented Generation (RAG) and natural language analytics. What we are looking for in our candidate Essential Proficiency in Python and SQL, with experience in frameworks like Pandas, PySpark, and NumPy for large-scale data processing. Expertise in debugging and optimising distributed systems with a focus on scalability and reliability. Proven ability to design and implement scalable, fault More ❯

data tooling such as Synapse Analytics, Microsoft Fabric, Azure Data Lake Storage/One Lake, and Azure Data Factory. Understanding of data extraction from vendor REST APIs. Spark/Pyspark or Python skills a bonus or a willingness to develop these skills. Experience with monitoring and failure recovery in data pipelines. Excellent problem-solving skills and attention to detail. More ❯

development) Strong experience with CI/CD tools and pipelines for data science Solid understanding of AWS services (e.g. EC2, S3, Lambda, Glue) and CDK Proficient in Python and PySpark; SQL fluency Experience with MLflow or other model lifecycle tools Effective communicator and trainer - able to help others upskill Comfortable building internal tools and documentation Nice to Have: Experience More ❯

Experience with Agile/Scrum Framework. Excellent problem-solving and analytical skills. Excellent communication skills, both at a deep technical level and stakeholder level. Data Expert experience with Databricks (PySpark). Experience building and maintaining complex ETL Projects, end-to-end (ingestion, processing, storage). Expert knowledge and experience with data modelling, data access, and data storage techniques. Experience More ❯

practice Essential Experience: Proven expertise in building data warehouses and ensuring data quality on GCP Strong hands-on experience with BigQuery, Dataproc, Dataform, Composer, Pub/Sub Skilled in PySpark, Python and SQL Solid understanding of ETL/ELT processes Clear communication skills and ability to document processes effectively Desirable Skills: GCP Professional Data Engineer certification Exposure to Agentic More ❯

warehousing ETL/ELT pipelines Change Data Capture (CDC) and change tracking Stream processing Database design Machine Learning and AI integration Hands-on experience with: Azure Databricks Python/PySpark Microsoft SQL Server Azure Blob Storage Parquet file formats Azure Data Factory Proven experience building secure, scalable, and high-performing data pipelines. Ability to solve complex technical problems and More ❯

Engineer/Data Engineering role Large and complex datasets Azure, Azure Databricks Microsoft SQL Server Lakehouse, Delta Lake Data Warehousing ETL CDC Stream Processing Database Design ML Python/PySpark Azure Blob Storage Parquet Azure Data Factory Desirable: Any exposure working in a software house, consultancy, retail or retail automotive sector would be beneficial but not essential. More ❯

approaches Experience with data ingestion and ETL pipelines Curious, adaptable, and a natural problem solver Bonus points for: Experience in financial services, insurance, or reinsurance Familiarity with Databricks, Git, PySpark or SQL Exposure to cyber risk or large-scale modelling environments Ready to Apply for this exciting Data Scientist role? Send your CV to (see below) - I'd love More ❯

Data Factory or equivalent cloud ETL tools, with experience building scalable, maintainable pipelines is essential. Extensive experience as a senior data or integrations engineer. Hands on experience on Python, Pyspark or Spark in an IDE. Data Bricks highly preferred. Proven track record in complex Data Engineering environments, including data integration and orchestration. Experience integrating external systems via REST APIs More ❯

data modeling, and software architecture Data Science Library Knowledge: Deep understanding of key Data Science and Machine Learning libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow), with a preference for PySpark experience Model Productionisation: Experience in taking Machine Learning models from development to production CI/CD and MLOps Experience : Familiarity with Continuous Integration and Continuous Deployment pipelines, especially in More ❯

end-to-end ownership of demand delivery Provide technical guidance for team members Providing 2nd or 3rd level technical support About You Experience using SQL, SQL Server DB, Python & PySpark Experience using Azure Data Factory Experience using Data Bricks and Cloudsmith Data Warehousing Experience Project Management Experience The ability to interact with the operational business and other departments, translating More ❯

with cross-functional teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date with ML algorithms Bonus points Experience with Databricks and PySpark Experience with deep learning & large language models Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch) Experience working with AWS or another cloud platform (GCP/Azure) Additional More ❯

with cross-functional teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date with ML algorithms Bonus points Experience with Databricks and PySpark Experience with deep learning & large language models Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch) Experience working with AWS or another cloud platform (GCP/Azure) Additional More ❯

work wimulti-functionalnal teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date with ML algorithms Bonus points Experience with Databricks and PySpark Experience with deep learning & large language models Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch) Experience working with AWS or another cloud platform (GCP/Azure) Additional More ❯

work wimulti-functionalnal teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date with ML algorithms Bonus points Experience with Databricks and PySpark Experience with deep learning & large language models Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch) Experience working with AWS or another cloud platform (GCP/Azure) Additional More ❯

work wimulti-functionalnal teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date with ML algorithms Bonus points Experience with Databricks and PySpark Experience with deep learning & large language models Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch) Experience working with AWS or another cloud platform (GCP/Azure) Additional More ❯

classifiers, deep learning, or large language models Experience with experiment design and conducting A/B tests Experience building shared or platform-style ML systems Experience with Databricks and PySpark Experience working with AWS or another cloud platform (GCP/Azure) Additional Information Health + Mental Wellbeing PMI and cash plan healthcare access with Bupa Subsidised counselling and coaching More ❯

classifiers, deep learning, or large language models Experience with experiment design and conducting A/B tests Experience building shared or platform-style ML systems Experience with Databricks and PySpark Experience working with AWS or another cloud platform (GCP/Azure) Additional Information Health + Mental Wellbeing PMI and cash plan healthcare access with Bupa Subsidised counselling and coaching More ❯

architecture Ensuring best practices in data governance, security, and performance tuning Requirements: Proven experience with Azure Data Services (ADF, Synapse, Data Lake) Strong hands-on experience with Databricks (including PySpark or SQL) Solid SQL skills and understanding of data modelling and ETL/ELT processes Familiarity with Delta Lake and lakehouse architecture A proactive, collaborative approach to problem-solving More ❯

in a team leadership role. Experience with Agile/Scrum frameworks. Excellent problem-solving and analytical skills. Excellent communication skills, both technical and stakeholder level. Data Expertise with Databricks (PySpark). Experience building and maintaining complex ETL projects end-to-end. Expertise in data modeling, access, and storage techniques. Experience with relational and document databases. Strong understanding of data More ❯

Strong analytical and troubleshooting skills. Desirable Skills Familiarity with state management libraries (MobX, Redux). Exposure to financial data or market analytics projects. Experience with data engineering tools (DuckDB, PySpark, etc.). Knowledge of automated testing frameworks (Playwright, Cypress). Experience of WebAssembly. Python programming experience for data manipulation or API development. Use of AI for creating visualisations. Soft More ❯

term data strategy with a strong focus on data integrity and GDPR compliance To be successful in the role you will have Hands-on coding experience with Python or PySpark Proven expertise in building data pipelines using Azure Data Factory or Fabric Pipelines Solid experience with Azure technologies like Lakehouse Architecture, Data Lake, Delta Lake, and Azure Synapse Strong More ❯