301 to 325 of 842 ETL Jobs in London

at minimum) Deliver strong CI/CD pipelines for robust delivery of software Data pipeline development, including building, orchestrating and scaling; have experience with ETL frameworks Data integration and interoperability in complex environments Technical Expertise – (Nice to Haves) Background in deployment of AI models with large experimental requirements, rather than More ❯

at minimum) Deliver strong CI/CD pipelines for robust delivery of software Data pipeline development, including building, orchestrating and scaling; have experience with ETL frameworks Data integration and interoperability in complex environments Technical Expertise – (Nice to Haves) Background in deployment of AI models with large experimental requirements, rather than More ❯

containerised services. Ensure reliable model integration across real-time APIs and batch processing systems. Pipeline Automation & MLOps Use Apache Airflow (or similar) to orchestrate ETL and ML workflows. Leverage MLflow or other MLOps tools to manage model lifecycle tracking, reproducibility, and deployment. Create and manage robust CI/CD pipelines More ❯

to a range of stakeholders and flexible to work under time pressure to business needs, particularly around quarter end close deadlines. Proven experience with ETL, data warehousing, version control, and wider data controls. Excellent analytical and problem-solving skills, with the ability to interpret complex data sets and debug complex More ❯

and communicating timelines and expectations for delivery on an ongoing basis. In conjunction with the Director of Data and Head of Data Transformation Development (ETL Lead), scope out new work and confirm priorities to ensure the broader team is delivering high-value items consistently throughout the year. Oversee a team More ❯

actions, index/benchmark data, fund/account information. Awareness of typical technical landscape within modern enterprise SaaS Applications including MS Azure, Snowflake, SQL, ETL tools, and machine learning models. Knowledge of data vendors such as Bloomberg, Refinitiv, MSCI, etc., other index and ESG data providers. Hands-on experience with More ❯

visualization tools and best practices (ideally using Tableau) A n ability to manipulate data using SQL and/or Python Experience with low-code Extract Transform and Load (ETL) applications is preferrable (for example, Tableau Prep or Alteryx) Strong communication skills, with the ability to present technical concepts to non More ❯

DB objects as per the design and defined standards. Maintain/Write SQL database schemas and scripts, including views, stored procedures, dynamic queries and triggers. Extract, transform, and load (ETL) data from multiple databases to support reference data enhancements and new functionalities. Optimize database performance through indexing, query optimization, and More ❯

a structured way. Preferred Qualifications 1-3 years of using Python (or other scripting languages) for automation & data transformation. Experience managing data pipelines (e.g. extract-transform-load processes). Experience with AIML concepts. Advanced Excel proficiency (including the ability to create macros) a plus. More ❯

data migration requirements and ensure smooth data transition to the cloud platform. Develop and execute comprehensive test plans for data migrations, database implementations, and ETL processes. Perform data validation and ensure data integrity throughout the migration process. Implement integrated test automation to streamline testing procedures and increase efficiency. Utilize SQL More ❯

needs and business strategies. Cloud Architecture: Design and implement scalable, cost-effective architectures across AWS, Azure, or GCP environments. Data Engineering: Develop and manage ETL/ELT pipelines, data integration workflows, and implement CDC and delta load design for effective data management. SAP Tools: Lead SAP BW to SAP Datasphere More ❯

needs and business strategies. Cloud Architecture: Design and implement scalable, cost-effective architectures across AWS, Azure, or GCP environments. Data Engineering: Develop and manage ETL/ELT pipelines, data integration workflows, and implement CDC and delta load design for effective data management. SAP Tools: Lead SAP BW to SAP Datasphere More ❯

needs and business strategies. Cloud Architecture: Design and implement scalable, cost-effective architectures across AWS, Azure, or GCP environments. Data Engineering: Develop and manage ETL/ELT pipelines, data integration workflows, and implement CDC and delta load design for effective data management. SAP Tools: Lead SAP BW to SAP Datasphere More ❯

. Experience deploying solutions on customer infrastructure, including setting up CI/CD, databases, and containerized services. A solid understanding of data management and ETL processes; AI/ML experience is beneficial but not mandatory. Willingness to travel (up to 50%) to collaborate closely with client teams—onsite problem-solving More ❯

. Experience deploying solutions on customer infrastructure, including setting up CI/CD, databases, and containerized services. A solid understanding of data management and ETL processes; AI/ML experience is beneficial but not mandatory. Willingness to travel (up to 50%) to collaborate closely with client teams—onsite problem-solving More ❯

skills in Python and SQL Experience building NLP/ML models, particularly for text classification or sentiment analysis Background in developing data pipelines and ETL processes Proven ability to translate complex data models into business insights Experience working with large datasets (preferably e-commerce or review data) Strong communication skills More ❯

in a data environment. Understand data structures and data model (dimensional & relational) concepts like Star schema or Fact & Dimension tables, to design and develop ETL patterns/mechanisms to ingest, analyze, validate, normalize, and cleanse data. Understand and produce 'Source to Target mapping' (STTM) documents, containing data structures, business & data More ❯

science, machine learning, and business analytics Practical experience in coding languages eg. Python, R, Scala, etc.; (Python preferred) Proficiency in database technologies eg. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. pySpark, Hive, etc. Experienced working with structured and also unstructured data eg. Text, PDFs, jpgs, call recordings More ❯

science, machine learning, and business analytics Practical experience in coding languages eg. Python, R, Scala, etc.; (Python preferred) Proficiency in database technologies eg. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. pySpark, Hive, etc. Experienced working with structured and also unstructured data eg. Text, PDFs, jpgs, call recordings More ❯

science, machine learning, and business analytics Practical experience in coding languages eg. Python, R, Scala, etc.; (Python preferred) Proficiency in database technologies eg. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. pySpark, Hive, etc. Experienced working with structured and also unstructured data eg. Text, PDFs, jpgs, call recordings More ❯

translate business requirements into technical solutions. Triage and resolve complex customer issues, debugging across APIs, databases and services. Develop tooling and data pipelines for ETL projects. Recommend and implement optimisations in customer architecture and integrations for performance, scalability and maintainability. Contribute to internal documentation and reusable customer solutions libraries (FAQs More ❯

Knowledge (Snowflake, PostgreSQL, MSSQL, etc.). Scripting languages (Python, PowerShell). Data quality and resolving related processes Cloud Data Warehousing solutions and ELT/ETL solutions (e.g., Snowflake, DBT). Experience in working within an Agile environment. Experience with Automation, including Unit and Integration Testing. Knowledge of Cloud Concepts. For More ❯

Knowledge (Snowflake, PostgreSQL, MSSQL, etc.). Scripting languages (Python, PowerShell). Data quality and resolving related processes Cloud Data Warehousing solutions and ELT/ETL solutions (e.g., Snowflake, DBT). Experience in working within an Agile environment. Experience with Automation, including Unit and Integration Testing. Knowledge of Cloud Concepts. For More ❯

and dynamic team. Responsibilities: Collaborate with various squads within the data team on project-based work. Develop and optimize data models, warehouse solutions, and ETL processes. Work with Scala, Spark, and Java to handle large-scale data processing. Contribute to manual Databricks-like data processing solutions. Requirements: Minimum of More ❯

and dynamic team. Responsibilities: Collaborate with various squads within the data team on project-based work. Develop and optimize data models, warehouse solutions, and ETL processes. Work with Scala, Spark, and Java to handle large-scale data processing. Contribute to manual Databricks-like data processing solutions. Requirements: Minimum of More ❯