26 to 50 of 169 PySpark Jobs

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 ❯

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 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 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 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 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

Experience with graph technology and/or algorithms, understanding of NLP algorithms Our technology stack Python and associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOp/DevOps: Terraform, Docker, Airflow, MLFlow, NewRelic The interview process Recruiter Call (30 minutes) Meeting a Machine Learning Manager(30 minutes 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

modelling techniques + data integration patterns. Experience of working with complex data pipelines, large data sets, data pipeline optimization + data architecture design. Implementing complex data transformations using Spark, PySpark or Scala + working with SQL/MySQL databases. Experience with data quality, data governance processes, Git version control + Agile development environments. Azure Data Engineer certification preferred -eg More ❯

modelling techniques + data integration patterns. Experience of working with complex data pipelines, large data sets, data pipeline optimization + data architecture design. Implementing complex data transformations using Spark, PySpark or Scala + working with SQL/MySQL databases. Experience with data quality, data governance processes, Git version control + Agile development environments. Azure Data Engineer certification preferred -eg 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 ❯

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 ❯

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 ❯