76 to 100 of 2,433 SQL Jobs in London

within a globally-distributed team A background in some of the following a bonus: Java experience Python experience Ruby experience Big data technologies: Spark, Trino, Kafka Financial Markets experience SQL: Postgres, Oracle Cloud-native deployments: AWS, Docker, Kubernetes Observability: Splunk, Prometheus, Grafana For more information about DRW's processing activities and our use of job applicants' data, please view our More ❯

Commercial/Procurement Analytics. Experience in SAP (S/4 Hana). Experience with Spark, Databricks, or similar data processing tools. Stron g technical proficiency in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and big data technolo g ies (e. g ., Hadoop, Spark, Kafka). Proficiency in More ❯

Commercial/Procurement Analytics. Experience in SAP (S/4 Hana). Experience with Spark, Databricks, or similar data processing tools. Stron g technical proficiency in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and big data technolo g ies (e. g ., Hadoop, Spark, Kafka). Proficiency in More ❯

amazing process management skills You'll need Advanced level of data literacy, preferably with experience as either Business Analyst, BI Analyst, Data Analyst or Process Analyst Strong Data Skills: SQL, spreadsheets, data visualisation/BI tools (e.g. Looker), and Python/R for more advanced analysis. Business Acumen: Understanding of business processes, financial concepts, macroeconomic trends, and industry-specific trends. More ❯

approaches and clear, confident recommendations.Manage projects end-to-end, from scoping through to delivering outputs that land with impact. What We're Looking For: Must-Haves: Strong proficiency in SQL for querying and transforming data, plus advanced Excel skills. Hands-on experience with BI/visualisation tools (Quicksight, Tableau, Power BI, Looker). Comfort working with large, complex datasets from More ❯

excellent communication skills with a consultative approach and a strong interest in influencing stakeholders. Tool experience required: Strong data visualisation using Power BI and coding ability using either normalisation, SQL, or Python). Desirable: Experience working in a Data warehouse, or lake environments e.g. Snowflake, Redshift, DataBricks, and ELT and data pipelines e.g. dbt Familiar with predictive analytics techniques Please More ❯

excellent communication skills with a consultative approach and a strong interest in influencing stakeholders. Tool experience required: Strong data visualisation using Power BI and coding ability using either normalisation, SQL, or Python). Desirable: Experience working in a Data warehouse, or lake environments e.g. Snowflake, Redshift, DataBricks, and ELT and data pipelines e.g. dbt Familiar with predictive analytics techniques Please More ❯

Power BI Engineer - ETL Processes, Data Warehouse, Business Intelligence, Analytics, Reporting, SQL, Investment Management - Permanent - London/Hybrid Our client, an Investment Management firm is scaling its Business Applications team and are now seeking to hire a Power BI Developer to support high-impact reporting and insights across the business. The successful candidate will be tasked with designing and building More ❯

excellent communication skills with a consultative approach and a strong interest in influencing stakeholders. Tool experience required: Strong data visualisation using Power BI and coding ability using either normalisation, SQL, or Python). Desirable: Experience working in a Data warehouse, or lake environments e.g. Snowflake, Redshift, DataBricks, and ELT and data pipelines e.g. dbt Familiar with predictive analytics techniques Please More ❯

excellent communication skills with a consultative approach and a strong interest in influencing stakeholders. Tool experience required: Strong data visualisation using Power BI and coding ability using either normalisation, SQL, or Python). Desirable: Experience working in a Data warehouse, or lake environments e.g. Snowflake, Redshift, DataBricks, and ELT and data pipelines e.g. dbt Familiar with predictive analytics techniques Please More ❯

Proficiency in ETL processes is mandatory Experience building components for enterprise data platforms (data warehouses, Operational Data Stores, API access layers, file extracts, user queries) Hands-on experience with SQL, Python, Spark, Kafka Excellent communication skills, with proficiency in verbal and written English About this Job This role involves developing and maintaining real-time data processing pipelines for enterprise customer More ❯

engineering to drive continuous improvement. What You'll Bring A passion for data, a growth mindset, and an ability to excel in a dynamic environment. Proficiency in dbt and SQL . Experience with big data technologies, such as Snowflake or comparable solutions. Familiarity with cloud-based data solutions, ideally on AWS , GCP , or Azure . Strong knowledge of data modeling More ❯

cloud storage platforms. Experience designing data schemas and analytical databases. Use of AI tools to streamline development and debugging. Strong grasp of algorithmic thinking and performance optimisation. Proficiency with SQL and NoSQL databases such as PostgreSQL and Cassandra. Experience with systems like Kafka or RabbitMQ. Ability to build and manage ETL pipelines using tools like Airflow. This role is an More ❯

cloud storage platforms. Experience designing data schemas and analytical databases. Use of AI tools to streamline development and debugging. Strong grasp of algorithmic thinking and performance optimisation. Proficiency with SQL and NoSQL databases such as PostgreSQL and Cassandra. Experience with systems like Kafka or RabbitMQ. Ability to build and manage ETL pipelines using tools like Airflow. This role is an More ❯

previous experience Be a graduate or of graduate calibre, will have a technology background, and hold a formal project management qualification. Technical proficiencies: .NET stack, C#, Python, React, Angular, SQL Experience in CI/CD pipelines, GitHub projects, GitHub Enterprise Server, Azure DevOps, container technologies (Docker, Kubernetes etc.,) and API gateway Proven track record of managing and delivering projects, ideally More ❯

/CD, and infrastructure-as-code Requirements 7+ years in data architecture or senior engineering roles Strong hands-on experience with Azure Databricks and Azure Data Factory Proficient in SQL, Python , and Spark Expertise in data modelling and architectural patterns for analytics (e.g., lakehouse, medallion, dimensional modelling) Solid understanding of cloud security, private networking, GDPR, and PII compliance Excellent communication More ❯

/CD, and infrastructure-as-code Requirements 7+ years in data architecture or senior engineering roles Strong hands-on experience with Azure Databricks and Azure Data Factory Proficient in SQL, Python , and Spark Expertise in data modelling and architectural patterns for analytics (e.g., lakehouse, medallion, dimensional modelling) Solid understanding of cloud security, private networking, GDPR, and PII compliance Excellent communication More ❯

documentation activities throughout the lifecycle Identify system inefficiencies and lead enhancements using innovative solutions Skills & Experience: Proven experience in senior data engineering roles, preferably within regulated industries Expertise in SQL, Snowflake, DBT Cloud, and CI/CD pipelines (Azure DevOps) Hands-on with ETL tools (e.g. Matillion, SNP Glue, or similar) Experience with AWS and/or Azure platforms Solid More ❯

a plus/• Working knowledge of CRM's interoperability capability with MS Office, MS Office 365, SharePoint, Azure and MS BI Stack • C#/VB.net, ADO.Net, XML, T/SQL, JQuery, JavaScript, Web Services, ASP.NET, and Silverlight skills • Experience in leading a Team • PowerApps Preferred • Planning and Prioritization skills • Experience in capturing requirements related to internal/external consulting, documenting More ❯

visualization using Tableau, Quicksight, or similar tools - Experience with data modeling, warehousing and building ETL pipelines - Experience in Statistical Analysis packages such as R, SAS and Matlab - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling PREFERRED QUALIFICATIONS - Experience with AWS solutions such as EC2, DynamoDB, S3, and More ❯

documentation activities throughout the lifecycle ·Identify system inefficiencies and lead enhancements using innovative solutions Skills & Experience: ·Proven experience in senior data engineering roles, preferably within regulated industries ·Expertise in SQL, Snowflake, DBT Cloud, and CI/CD pipelines (Azure DevOps) ·Hands-on with ETL tools (e.g. Matillion, SNP Glue, or similar) ·Experience with AWS and/or Azure platforms ·Solid More ❯

data analysis, e.g. sentiment analysis, to craft a coherent customer satisfaction and pain-point analysis Experience conducting adoption funnel analysis, pareto analysis and customer segmentation analysis Strong proficiency in SQL and Python Hands-on experience with BI and analytics tools (Power BI, Pendo) Understanding of key SaaS metrics and customer lifecycle analytics Excellent communication skills with the ability to translate More ❯

and seek process improvements. Establish best practices and repeatable processes for technology use. How You'll Do It To succeed, you should have: A strong educational background Proficiency in SQL for database querying and modeling Understanding of financial terminology Experience with BI reporting and visualization tools (Looker, PowerBI, Tableau) Knowledge of ETL tools like Alteryx An interest in sports and More ❯

equivalent practical experience. 8+ years of professional experience in software development, with demonstrable technical leadership. Essential Experience : Strong hands-on experience with Node.js, TypeScript/JavaScript, React (or Remix), SQL/NoSQL databases, and CSS. Proven track record of leading Agile development teams. Experience designing and building cloud-based, scalable applications. Familiarity with test-driven development (TDD) and version control More ❯

Expertise: - Deep understanding of data engineering principles and best practices, including data modeling, observable ETL/ELT processes, data warehousing, and data governance. - Proficiency in data manipulation languages (e.g., SQL/DBT) and programming languages relevant to data engineering (e.g., Python). - Experience with a variety of data processing frameworks and technologies, including cloud-based data services. Software Engineering Practices More ❯