101 to 125 of 190 PySpark Jobs

cross functional teams entrusted with business-critical platforms.Desirable skills & experienceWorking to an Agile methodology and familiarity with Azure DevOpsDeep automation knowledge with PythonSkilled in Pyspark and SynapseExperience with data modelling and visualisation in Power BI (or alternative)A strong understanding of architecting data platforms, BI, MI, or analytics solutionsStrong more »

Ability to optimise workflows and analysis for map reduce processing Experience with BI software (Power BI, Tableau, Qlik Sense) Any experience with data engineering, PySpark, Databricks, Delta Lakes beneficial Confident presenting complex problems in ways suitable to target audience Experience leading or managing a small analysis team Familiarity working more »

expertise and requirements. You have A BSc or MSc in computer science or related fields. Expertise in Python, including popular Python libraries: NumPy, Pandas, PySpark and frameworks: Django, Django Rest Framework, FastAPI Hands-on experience with both relational (e.g. PostgreSQL) and non-relational databases (e.g. Elasticsearch, Redis). Strong more »

learning, probability, statistics, and quantitative risk modelling. High proficiency in Python and SQL. Experience with big data technologies and tools such as Databricks and PySpark is highly desirable. Essential experience in Probabilistic Risk Modelling. Highly desirable experience with Monte Carlo, Capula, Gamma, Statistical modelling, financial modelling, and Stochastic modelling. more »

and industry standards for the organization. Strong experience on Azure cloud services like Azure, ADF, ADLS, Synapse Proficiency in querying languages such as SQL, Pyspark, Python and familiarity with data visualization tools (e.g. Power BI). Strong communication skills to gather the business requirements from stakeholder and propose best more »

that are comfortable with terms like; Statistical Models, Computer Vision, Predictive Analytics, Data Visualization, Large Language Models (LLM), NLP, AI, Machine Learning, MLOPs, Python, Pyspark, and Azure. Flexible Working : The role is 60% work from home Sponsorship : Sadly sponsorship isn't available for these roles. About You: Bachelors Degree more »

Quality and Information Security principles Experience with Azure, ETL Tools such as ADF and Databricks Advanced Database and SQL skills, alng with SQL, Python, Pyspark, Spark SQL Strong understanding of data model design and implementation principles Data warehousing design patterns and implementation Benefits : £50-£60k DOE Mainly home based more »

a complete greenfield re-architecture from the ground up in Microsoft Azure. The Tech you'll be playing with: Azure Data Factory Azure Databricks PySpark SQL DBT What you need to bring: 1-3 year's experience in building Data Pipelines SQL experience in data warehousing Python experience would more »

Proficiency in modern programming languages and database querying languages. Comprehensive understanding of the Software Development Life Cycle and Agile methodologies. Familiarity with Python or PySpark and cloud technologies like AWS, Kubernetes, and Spark is highly desirable. Ideal Candidate: Someone with a knack for innovative solutions and a commitment to more »

Glue and SageMaker Infrastructure-as-Code tools and approaches (we use the AWS CDK with CloudFormation) Data processing frameworks such as pandas, Spark and PySpark Machine learning concepts like model training, model registry, model deployment and monitoring Development and CI/CD tools (we use GitHub, CodePipeline and CodeBuild more »

Skills and experience we’re looking for: Proven track record productionising data pipelines at scale Hands-on experience or understanding of: Python, Spark (e.g., PySpark, Spark tuning, Spark UI); Data Engineering technologies and principles (e.g., Data Lakes, Batch/Streaming); Cloud technologies and principles (e.g., Kubernetes, EMR, S3) Understanding more »

of Python Experience developing in the cloud (AWS preferred) Solid understanding of libraries like Pandas and NumPy Experience in data warehousing tools like Snowflake, Pyspark, Databricks Commercial experience with performant database programming in SQL Capability to solve complex technical issues, comprehending risks prior to the circumstance. Please apply today more »

field like engineering, mathematics, statistics or operations research is a must. Masters in a relevant field will be an added advantage.Preferred Qualifications:Knowledge of PySpark, Hive & other big data tools & techniques.Experience with data visualization tools, such as Tableau, Power BI, or similar tools, to efficiently communicate complex analyses and more »

experience working directly with C-Suite execs. Technical Expertise Needed At least 3 years Databrick s (must have) Proven experience delivering scalable data pipelines PySpark SQLDevOps/DataOps/CICD Expertise in designing, constructing, administering, and maintaining data warehouses and data lakes Data Modelling/Data Architecture Data Migration more »

data integration pipelines, transformations, pipeline scheduling, Ontology, and applications in Palantir Foundry Design, develop and deploy data solutions in Palantir with excellent skills in PySpark and Spark SQL for data transformations Experience in designing and building interactive data applications working with Ontology, actions, functions, object views, automate, indexing, data more »

for: -Data Engineering + Data Science Experience -Strong ETL Experience -Experience with Computer Vision -Experience in Remote Sensing highly desirable Stack: Python, PyTorch, AirFlow, PySpark (equivalent tools are fine more »

Modeling within a cloud-based data platform Strong experience with SQL Server Azure data engineering stack, including Azure Synapse and Azure Data Lake Python, PySpark and T-SQL In return you will be offered a competitive salary and benefits package, remote working options and an opportunity to work with more »

in retail/marketing but not requiredCandidates should be looking to work in a fast paced startup feel environmentTech across: Python, SQL, AWS, Databricks, PySpark, AB Testing, MLFlow, APIsApply below!CONTACTIf you can’t see what you’re looking for right now, send us your CV anyway – we’re more »

experience-related problems such as workforce management, demand forecasting, or root cause analysis Strong visualisation skills including experience with Tableau Familiarity with Databricks and PySpark for data manipulation and analysis Familiarity with Git-based source control methodologies, including branching and pull requests A self-starter, passionate about converting data more »

experience leading a data engineering team. Key Tech: - AWS (S3, Glue, EMR, Athena, Lambda) - Snowflake, Redshift - DBT (Data Build Tool) - Programming: Python, Scala, Spark, PySpark or Ab Initio - Data pipeline orchestration (Apache Airflow) - Knowledge of SQL This is a 6 month initial contract with a trusted client of ours. more »

data experience Data inventory and data familiarisation Efficient data ingestion and ingestion pipelines Data cleaning and transformation Databricks (ideally with Unity Catalog) Python and PySpark CI/CD (ideally with Azure Devops) Unit testing (PyTest) If you have the above experience and are looking for a new contract role more »

requiring 2-3 days onsite) and is paying up to £110,000 per annum Key Skills Strong commercial experience with Python/SQL/PySpark Knowledge of converting business requirements to engineering processes Azure environment - Data Bricks & Data Factory Industry experience with Insurance would be highly desirable The processing more »

come with scaling a company • The ability to translate complex and sometimes ambiguous business requirements into clean and maintainable data pipelines • Excellent knowledge of PySpark, Python and SQL fundamentals • Experience in contributing to complex shared repositories. What’s nice to have: • Prior early-stage B2B SaaS experience involving client more »

with operational stakeholders propose how a machine learning model could benefit the process, and finally building the model to realise the benefit. Experience using PySpark to process large scale data would be advantageous, particularly use within the Databricks platform. Familiarity with insurance claims data is preferred but not essential. more »

with operational stakeholders propose how a machine learning model could benefit the process, and finally building the model to realise the benefit. Experience using PySpark to process large scale data would be advantageous, particularly use within the Databricks platform. Familiarity with insurance claims data is preferred but not essential. more »