101 to 125 of 409 Permanent Databricks Jobs

scripting or programming experience Strong conceptual skills, logical/analytical thinking & problem-solving skills Desirable Experience with Infrastructure as Code, for automation and configuration management Knowledge and experience of Databricks THE PACKAGE A Competitive starting salary with annual pay reviews. 25 Days holiday plus bank holidays. Plenty of opportunity for progression. Flexibility for hybrid working. Health care and medical insurance More ❯

Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. Experience with deploying services in Docker and Kubernetes Experience in creating production grade coding and SOLID programming principles, including test-driven development (TDD) approaches Experience in programming More ❯

Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. Experience with deploying services in Docker and Kubernetes Experience in creating production grade coding and SOLID programming principles, including test-driven development (TDD) approaches Experience in programming More ❯

optimization and distributed SQL processing. Proficiency in working with Parquet Files for efficient data storage and retrieval. Hands-on experience with Airflow for orchestrating complex data workflows. Familiarity with Databricks Medallion model. Familiarity with OpenMetaData for metadata management and data governance. Experience working with streaming and batch data processing frameworks is a plus. Due to US Government Contract Requirements, only More ❯

Pittsburgh, PA. What Youll Do This is a full stack data science opportunity that will get to work with some of the latest technologies in the Azure Cloud including Databricks, Azure Machine Learning, and Cognitive Services. You will have the opportunity to drive the full data science lifecycle from strategy to data preparation and algorithm development to communicating the answer More ❯

to learn. Technical Skills: Degree or equivalent experience in data science, analytics, or a related field. Proven experience of creating and maintaining data pipelines. Experience of Advanced Excel, Azure Databricks, Advanced SQL, working knowledge of PowerBI, and exposure to GIS. GDPR awareness and compliance. Desirable: Understanding and exposure to databases, interfaces, business systems and work force management solutions Knowledge of More ❯

tools ElasticSearch and OpenSearch .NET, C#, Javascript, and Java Terraform Experience developing and maintaining components in AWS SpringBoot framework Experience with ELK stack, OpenSearch, SonarQube, Cypress, PowerShell, C#, and Databricks Experience with Docker, SQL, Angular, Spring Boot, Nifi, AWS, python, scala, shell scripting, and XML processing Experience in AWS solution architecture Experience as a scrum participant and software release processes More ❯

Notebooks, Power BI). Lead and manage the QA effort across multiple agile teams. Drive the development and maintenance of automated testing for: 1-PySpark notebooks in Fabric/Databricks 2-Data pipelines and transformations 3-Delta tables and lakehouse validation Embed testing into CI/CD pipelines (Azure DevOps or GitHub Actions). Ensure quality gates are enforced through More ❯

field with 5+ years experience. PREFERRED QUALIFICATIONS Full-stack development experience e.g. React/Angular and integration with backend. AWS experience or working knowledge of AWS partner solutions like Databricks or Snowflake. Expertise of implementing GenAI in production including LLMs, RAG architectures, vector databases. Experience with automation and scripting (e.g., Terraform, Python). Knowledge of security and compliance standards (e.g. More ❯

problems we can help solve together. Knowledge & experience needed: Excellent ability in R or Python, to write clear, logical, documented code as data solutions Experience working with Azure (Cloud), Databricks Experience working with real-world data, including spatial data Understanding of data product development frameworks Highly numerate with excellent analytical and problem-solving skills, including experience of analysing and accurately More ❯

lead data role and then into a management Very strong technical skills that will include - SQL, SSIS, SSRS, SAS - Power BI, Power Platform - Azure Data Factory, Azure Data Lake, Databricks A good understanding of dimensional modelling techniques, including Kimball's Business Development Lifecycle Ability to design hybrid data solutions across on-prem and cloud data sources Expert with data engineering More ❯

skills and the ability to work collaboratively in a team environment. • Eagerness to learn and grow in the field of data engineering and cloud technologies. Preferred Qualifications: • Exposure to Databricks Runtime and Spark Livy. • Basic understanding of location data types and spatiotemporal data. More ❯

Preferred Qualifications Exposure to machine learning workflows, model lifecycle management, or data engineering platforms. Experience with distributed systems, event-driven architectures (e.g., Kafka), and big data platforms (e.g., Spark, Databricks). Familiarity with banking or financial domain use cases, including data governance and compliance-focused development. Knowledge of platform security, monitoring, and resilient architecture patterns. More ❯

into a management (mentoring, coaching, team development etc) Very strong technical skills that will include - SQL, SSIS, SSRS, SAS, Power BI, Power Platform, Azure Data Factory, Azure Data Lake, Databricks A good understanding of dimensional modelling techniques, including Kimball's Business Development Lifecycle Ability to design hybrid data solutions across on-prem and cloud data sources Expert with data engineering More ❯

closely with the data science team to integrate modelling approaches and techniques Key Skills and Experience: Previous experience as a DevOps/MLOps engineer Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud) Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and More ❯

closely with the data science team to integrate modelling approaches and techniques Key Skills and Experience: Previous experience as a DevOps/MLOps engineer Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud) Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and More ❯

in SQL Server, Azure Cosmos DB and Apache Spark. Communication: Strong communication and organisational skills. Advantageous Skills The following skills and experiences are considered strong advantageous: Experience in Azure Databricks is a strong advantage. Experience in Azure Data Factory is a strong advantage. Experience in .NET and Entity Framework is a strong advantage. Experience in Python is a strong advantage. More ❯

Azure Data Explorer . • Experience working with data in a variety of structured and unstructured formats. • Experience with data visualization tools, computing platforms, and applications such as: Juptyer, Elasticsearch, DataBricks, Apache Zeppelin, Kibana, and/or Tableau • Experience supporting the development of AI/ML algorithms, such as natural language processing in a production environment • Experience configuring and utilizing data More ❯

processes. Proficient in SQL scripting, writing complex queries, and test script development. Experience with structured and unstructured data testing. Hands-on knowledge of Azure data services like Data Factory, Databricks, Synapse, Cosmos DB, and Data Lake. Familiarity with data testing automation tools and frameworks. Domain knowledge in Insurance is a plus. Skilled in Python and PySpark for scripting and automation. More ❯

identify risks, without prompting Proficient at communicating results in a concise manner both verbally and written Desirable Hands-on experience in the cloud platform and tools (i.e. Azure, AWS, Databricks) Insurance or financial services experience Knowledge and awareness of the latest tools, techniques and technology across the analytics marketplace Behaviours: Team player Self-motivated with a drive to learn and More ❯

identify risks, without prompting Proficient at communicating results in a concise manner both verbally and written Desirable Hands-on experience in the cloud platform and tools (i.e. Azure, AWS, Databricks) Insurance or financial services experience Knowledge and awareness of the latest tools, techniques and technology across the analytics marketplace Behaviours: Team player Self-motivated with a drive to learn and More ❯

passion for new technologies Experience in startups or top-tier consultancies is a plus Nice to Have: Familiarity with dashboarding tools, Typescript, and API development Exposure to Airflow, DBT, Databricks Experience with ERP (e.g. SAP, Oracle) and CRM systems What's On Offer: Salary: £50,000-£75,000 + share options Hybrid working: 2-3 days per week in a More ❯

passion for new technologies Experience in startups or top-tier consultancies is a plus Nice to Have: Familiarity with dashboarding tools, Typescript, and API development Exposure to Airflow, DBT, Databricks Experience with ERP (e.g. SAP, Oracle) and CRM systems What's On Offer: Salary: £50,000-£75,000 + share options Hybrid working: 2-3 days per week in a More ❯

projects involving data transformation and loading into Databricks. Strong understanding of data pipeline architectures and best practices. Proficiency in programming languages such as Python, SQL, or Scala. Experience with Databricks and related tools and technologies. Excellent problem-solving and analytical skills. Strong communication and collaboration abilities. Preferred Skills: Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud). More ❯

data security (e.g. RLS); other reporting tools a bonus. Strong background in data analytics, modelling, and pipeline development, with hands-on proficiency in SQL, Python, and cloud platforms (Azure, Databricks, etc.). Demonstrated ability to work closely with stakeholders to translate business needs into actionable insights, user stories, and high-impact reporting solutions. Must thrive in Agile environments, with a More ❯