1 to 25 of 86 Remote Databricks Jobs in London

testing methodologies and development team collaboration Experience working with Power BI and DAX Strong documentation, communication, and stakeholder engagement skills Preferred Qualifications: Experience with Lakehouse architecture, Delta Lake, or Databricks Exposure to Agile/Scrum working practices Microsoft certifications (e.g., Azure Data Engineer Associate) Background in consulting or professional services Understanding of data governance and data security principles Nice to More ❯

can influence promised outcomes. Drive high client value and broaden relationships at senior levels with current and prospective clients. Our Tech Stack Cloud: Azure, sometimes GCP & AWS Data Platform: Databricks, Snowflake, BigQuery Data Engineering tools: Pyspark, Polars, DuckDB, Malloy, SQL Infrastructure-as-code: Terraform, Pulumi Data Management and Orchestration: Airflow, dbt Databases and Data Warehouses: SQL Server, PostgreSQL, MongoDB, Qdrant More ❯

to clean, transform, and enrich data from various sources. Ensure that pipelines are automated, scalable, and fault-tolerant to accommodate large volumes of data. Experience with Notebooks (e.g., Jupyter, Databricks) for data exploration, analysis, and reporting. Design and optimise data workflows to streamline key processing tasks, enhancing operational efficiency. API Integration & Data Ingestion: Integrate external and internal APIs to ingest More ❯

as an Azure Data Architect or Lead Data Engineer. Expertise in Microsoft Fabric, as well as in one or more of the following platforms: Azure Synapse Analytics and Azure Databricks, and supporting data technologies like Power BI, Microsoft Purview, Azure SQL Database, Azure Data Lake, etc. Excellent stakeholder engagement and communication skills. Able to consult, advise, architect and estimate project More ❯

with SQL and large-scale datasets Excellent communication skills and ability to present complex ideas to non-technical stakeholders Experience with cloud platforms (AWS, GCP, Azure) and tools like Databricks, Snowflake, or BigQuery Desirable Skills Familiarity with MLOps, model monitoring, and production deployment Experience in a specific domain (e.g., marketing, operations, fraud, personalization, NLP) is a plus Hands-on experience More ❯

production environments Demonstrated ability to translate ambiguous business problems into scalable, production-ready data science solutions Hands-on experience with cloud platforms (AWS, GCP, Azure) and tools such as Databricks, Snowflake, and BigQuery Exceptional communication and stakeholder management skills, with the ability to influence decision-making across technical and non-technical teams Desirable skills Familiarity with real-time model serving More ❯

investment team on tech delivery Strong understanding of Python, with libraries/frameworks such as Pandas, NumPy, and PySpark Strong understanding of distributed computing, with experience using frameworks like Databricks Strong experience with Azure or other cloud platforms (AWS) Strong experience building data pipelines or ETL tools and Orchestration frameworks such as Airflow Strong experience and appreciation of CI/ More ❯

documentation and knowledge sharing including data flow/mappings, data dictionary, ERD related to the data solutions. Minimum Criteria: Building scalable data pipelines, utilising Azure Data Factory, Synapse and Databricks to build and maintain robust data pipelines that process and transform data efficiently. Experience with large data migration (essential) Designing data models: Creating and optimising data models, writing complex SQL More ❯

such as private endpoints, Firewalls, NSGs, NAT gateways and route tables. Strong understanding of security best practices within Azure and ideally AWS. Experience of configuring cloud data services (preferably Databricks) in Azure and ideally AWS. Excellent communication and collaboration skills, with the ability to work across multiple Should this position be of interest please submit your CV and I will More ❯

You will be adaptable and able to work with different tools and technologies, depending on the client and project needs but will ideally possess stength in: MS Fabric stack Databricks Azure SQL Tableau/Power BI A knowledge of data modelling and of general IT architecture and systems integration is also required. Other technologies such as Azure Data Factory, RedShift More ❯

You will be adaptable and able to work with different tools and technologies, depending on the client and project needs but will ideally possess stength in: MS Fabric stack Databricks Azure SQL Tableau/Power BI A knowledge of data modelling and of general IT architecture and systems integration is also required. Other technologies such as Azure Data Factory, RedShift More ❯

within the insurance sector, ideally with London Market experience. Strong knowledge of insurance data models, including policy, claims, and risk-related structures. Expertise in Azure Cloud Services (Data Factory, Databricks, Key Vault, Azure SQL) and data warehousing methodologies (Kimball, Inmon). Proficiency in T-SQL for data transformation and summarisation, with Python skills for building data pipelines. Advanced Excel skills More ❯

Experience with go-to-market activities, RFI/RFP responses, and proposal materials. TOGAF or equivalent certification; cloud certifications (AWS/Azure); data & AI tooling (e.g., Azure Fabric, Snowflake, Databricks). Experience with Data Mesh and data governance platforms (e.g., Collibra, Informatica). Ability to develop a common language for data, data models, data dictionaries, vocabularies, taxonomies, or ontologies. Experience More ❯

engineering roles, ideally within consumer tech, logistics, or e-commerce. Strong proficiency in Python, SQL, and machine learning frameworks. Experience with cloud platforms (Azure, AWS, GCP) and tools like Databricks, DBT, Airflow, or Terraform. Familiarity with AI/ML applications and modern analytics tooling. Excellent communication skills and ability to work independently in a fast-paced environment. Why Join? Be More ❯

small, high-performing team. What We're Looking For Hands-on Palantir Foundry expertise or transferable, client facing data engineering experience with large-scale data platforms such as: Snowflake, Databricks, AWS Glue/Redshift, Google BigQuery Software engineering skills in Python, Java, or TypeScript/React. Strong data modelling, pipeline development, and API design experience. Excellent problem-solving and communication More ❯

small, high-performing team. What We're Looking For Hands-on Palantir Foundry expertise or transferable, client facing data engineering experience with large-scale data platforms such as: Snowflake, Databricks, AWS Glue/Redshift, Google BigQuery Software engineering skills in Python, Java, or TypeScript/React. Strong data modelling, pipeline development, and API design experience. Excellent problem-solving and communication More ❯

a data validation framework to automate quality control processes Requirements Over 3+ years of hands-on Python development experience for production systems Proficient in data cloud computing technologies (EMR, Databricks) within leading cloud platforms (AWS, Google Cloud, or Azure) Skilled in designing and implementing data pipelines using distributed storage platforms Demonstrated analytical skills and structured approach to software design Have 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 ❯

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 ❯

users in line with security standards Qualifications Experience in a data, operations, or analytics-focused role Familiarity with BI and reporting platforms such as Power BI, Datorama, Data Studio, Databricks, SQL Strong communication skills and a collaborative, solutions-focused mindset An organised, proactive approach-comfortable working across teams and timelines Excitement for new technology, data storytelling, and digital marketing innovation More ❯

Strong proficiency in SQL scripting, including writing and executing complex queries. Hands-on experience with structured and unstructured data testing. Good understanding of Azure data services , including Data Factory, Databricks, Synapse (Azure SQL DW), Cosmos DB, and Azure Data Lake. Knowledge of data testing concepts and best practices within data warehouse environments. Hands-on experience with Python/PySpark scripting More ❯

including 4+ years in pre-sales/solutioning. Banking transformation expertise (regulatory reporting, finance/data modernisation). Strong cloud/data architecture skills (Azure/AWS/GCP, Databricks, Snowflake, Synapse). Data governance expertise and RFP/RFI leadership. Why apply? Senior, strategic role with real influence. Opportunity to lead major banking transformation initiatives. Excellent package and hybrid More ❯

including 4+ years in pre-sales/solutioning. Banking transformation expertise (regulatory reporting, finance/data modernisation). Strong cloud/data architecture skills (Azure/AWS/GCP, Databricks, Snowflake, Synapse). Data governance expertise and RFP/RFI leadership. Why apply? Senior, strategic role with real influence. Opportunity to lead major banking transformation initiatives. Excellent package and hybrid More ❯

GCP/BigQuery (or similar cloud platforms). Education: Degree in Investments, Accounting, Actuarial Science, or related discipline from a UK university. Nice to Have Experience with dbt or Databricks . Background in life insurance, reinsurance, or large-scale investment projects. Interview Process Stage 1: Initial 20-30 min screening call (CV and experience overview). Stage 2: 1-hour More ❯

teams through complex transformation programmes. Shape enterprise data strategies, governance frameworks, and operating models. Engage in high-level conversations around AI, GenAI, and modern data platforms like Snowflake and Databricks - you don't need to be a deep technical SME, but you'll need to understand the landscape. Drive client growth by identifying opportunities, building relationships, and offering the right More ❯