1 to 25 of 618 ETL Jobs in London

opportunity to grow your technical skills and gain valuable experience in a fast-paced environment.Key Responsibilities:Data Pipeline Development: Assist in building and maintaining ETL (Extract, Transform, Load) processes to integrate data from various sources into our Data Lakehouse.Data Visualisation: Develop and maintain dashboards and reports using Power BI, providing … data workflows, processes, and systems.SQL : Demonstrated ability to write complex SQL queries for data extraction, manipulation, and transformation. Experience in data integration tasks, including ETL (Extract, Transform, Load) processes, to consolidate data from multiple sources into a unified format.Python: Experience with Python programming for data manipulation, analysis, and automation. Understanding ...

data warehousing, business intelligence, and databases (Snowflake, ANSI SQL, SQL Server, T-SQL);Support programming/software development using Extract, Transform, and Load (ETL) and Extract, Load and Transform (ELT) tools, (dbt, Azure Data Factory, SSIS);Design, develop, enhance and support business intelligence systems primarily using Microsoft Power BI;Collect … Data Engineering;Knowledge of developing dimensional data models and awareness of the advantages and limitations of Star Schema and Snowflake schema designs;Solid ETL development, reporting knowledge based off intricate understanding of business process and measures;Knowledge of Snowflake cloud data warehouse, Fivetran data integration and dbt transformations is preferred ...

programmes and business functions. Qualifications & Experience:Essential ExperienceDemonstrable experience delivering data engineering solutions within complex project, programme, or enterprise environments.Strong experience designing and maintaining ETL/ELT pipelines, data integration processes, and structured data platforms.Experience working with Microsoft Fabric, Azure Data Services, SQL, Power BI, or equivalent modern data platforms.Strong ...

and maintaining data pipelines, automation, and data processing workflows, including use of PySpark.Proficiency in SQL for querying, transformation, and analytical data processing.Solid understanding of ETL/ELT pipelines, data transformation patterns, and data integration concepts.Experience analyzing enterprise data sources to identify data relationships, transformations, and business rules.Experience building solutions ...

and accessibility of information.Data Platform Development: Builds and maintains scalable and robust data platforms to support analytics, machine learning, and business intelligence.Data Integration and ETL: Develops and optimizes ETL (Extract, Transform, Load) processes and data integration pipelines. Ensures efficient data flow across various sources and systems.Advanced File Processing: Develops extensible ...

and maintain data warehouse environments, such as:Azure Synapse AnalyticsSQL Server/Azure SQL DBSnowflake or BigQuery (optional, if used in hybrid environments)Monitor ETL performance and investigate slow-running queries and data load failures. Issue Investigation & RCAInvestigate job failures and performance issues across data pipelines, ML endpoints, and dashboards.Perform ...

Bachelor’s or master’s degree in computer science, Engineering, or a related technical field 5+ Years of hands-on experience in data engineering, ETL/ELT development, cloud-based data solutions, or data products for analytics, automation, or machine learning Deep expertise in AWS services, including S3, Lambda, Glue ...

data governance, lineage, security, and compliance controls within modern data platforms. Experience leading architecture decisions across complex stakeholder environments. Strong understanding of data pipelines, ETL/ELT frameworks, orchestration tooling, and data engineering best practices. Familiarity with technologies such as Spark, Python, SQL, Delta Lake, Unity Catalog, dbt, Azure Data ...

initiatives, and flag risks or dependenciesTECHNICAL SKILLS & EXPERTISEStrong data engineering skills: SQL (advanced), Python or PowerShell for data extraction, transformation, and automation; experience with ETL/ELT pipelinesDashboard development: Power BI (preferred), Tableau, Grafana, or equivalent BI tools — building interactive dashboards with drill-down, filtering, and alertingExperience with on-premises ...

lifecycle (SDLC) submitting work for technical test, cosmetic test and applying re-work when required.Dimensional Modelling (Kimball Methodology), database principles and ETL (Extract, Transform and Load).Coordinate and maintain the reporting requirements backlog, working with stakeholders to deliver value at the right time.Required to perform duties as BI System administrator ...

comfortable working independently, collaborating with business and technology stakeholders, and delivering high-quality solutions with minimal supervision.Key Responsibilities•Design, build and optimise scalable ETL/ELT data pipelines.•Develop and maintain solutions using Databricks, Python and SQL.•Support migration of data assets from legacy platforms into modern cloud-based architectures. ...

Business stakeholders. Data Engineering & Platforms Databricks Delta Lake Unity Catalog dbt Spark/PySpark Data pipeline development and optimisation Lakehouse architecture Data integration and ETL/ELT frameworks Data platform design and implementation Cloud Technologies AWS S3 Glue Airflow IAM Lambda (desirable) Data Modelling & Architecture Data Vault Kimball Data warehousing ...

data warehousing, data lakes, and lakehouse architectures. Hands-on experience with SQL and at least one programming language such as Python, Scala, or Java. ETL/ELT design and data pipeline orchestration. Streaming and event-driven data architectures. Agile and DevOps delivery methodologies applied to data platforms (DataOps).Expertise ...

data warehousing, data lakes, and lakehouse architectures. Hands‐on experience with SQL and at least one programming language such as Python, Scala, or Java. ETL/ELT design and data pipeline orchestration. Streaming and event-driven data architectures. Agile and DevOps delivery methodologies applied to data platforms (DataOps). Expertise ...

platform reliability and supportability. Collaborate with engineers, analysts and stakeholders to deliver practical solutions. Essential Skills Strong SQL and Snowflake experience. Data engineering and ETL/ELT development. Dimensional modelling (Kimball methodology). dbt development and engineering best practices. Azure Data Factory, Azure Functions and CI/CD. Python development ...

platform reliability and supportability. Collaborate with engineers, analysts and stakeholders to deliver practical solutions. Essential Skills Strong SQL and Snowflake experience. Data engineering and ETL/ELT development. Dimensional modelling (Kimball methodology). dbt development and engineering best practices. Azure Data Factory, Azure Functions and CI/CD. Python development ...

platform reliability and supportability. Collaborate with engineers, analysts and stakeholders to deliver practical solutions. Essential Skills Strong SQL and Snowflake experience. Data engineering and ETL/ELT development. Dimensional modelling (Kimball methodology). dbt development and engineering best practices. Azure Data Factory, Azure Functions and CI/CD. Python development ...

platform reliability and supportability. Collaborate with engineers, analysts and stakeholders to deliver practical solutions. Essential Skills Strong SQL and Snowflake experience. Data engineering and ETL/ELT development. Dimensional modelling (Kimball methodology). dbt development and engineering best practices. Azure Data Factory, Azure Functions and CI/CD. Python development ...

platform reliability and supportability. Collaborate with engineers, analysts and stakeholders to deliver practical solutions. Essential Skills Strong SQL and Snowflake experience. Data engineering and ETL/ELT development. Dimensional modelling (Kimball methodology). dbt development and engineering best practices. Azure Data Factory, Azure Functions and CI/CD. Python development ...

strategies.Data Platforms:- Hands-on experience with data lakes and lakehouse architectures.- Familiarity with big data processing frameworks like Spark.Data Engineering Knowledge:- Proven experience building ETL/ELT pipelines and using orchestration tools (Airflow, Azure Data Factory).- Understanding of JSON, XML, APIs, and data ingestion technologies.Cloud Experience:- Familiarity with cloud ...

data warehousing, data lakes, and lakehouse architectures. Hands-on experience with SQL and at least one programming language such as Python, Scala, or Java. ETL/ELT design and data pipeline orchestration. Streaming and event-driven data architectures. Agile and DevOps delivery methodologies applied to data platforms (DataOps). Expertise ...

e.g. Cloud, Azure, Databricks), and enterprise data and analytics ecosystems, including medallion architectures, data lakehouse designs, master data systems, legacy data warehouses, data engineering (ETL, ELT, CDC) for enterprise scale analytics) Experience with data product thinking, domain-oriented ownership or federated operating models Understanding of data standards and industry models ...

data manipulation and scripting.Data Engineering: Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop). Experience with ETL/ELT, data warehousing, and automated workflows for moving and processing data.Data Governance: Strong understanding and practical experience with data governance principles, policies, security, and privacy ...

Reference Data. Cloud Platforms: Microsoft Azure; AWS; GCP. Modern Data Platforms: Databricks; Microsoft Fabric; PostgreSQL. Data Integration: Azure Data Factory; API-led Integration; Kafka; ETL/ELT; Streaming and Event-Driven Architectures. Architecture & Modelling: TOGAF; DAMA; ArchiMate; Sparx Enterprise Architect. Data Governance: Microsoft Purview; Collibra; Informatica; Security by Design; Data ...

data architectural decisions, and high-quality "data mart" objects across functions like product, finance, or strategy.Pipeline Specialist: You possess extensive experience in engineering robust ETL/ELT processes and data pipelines, with a focus on curating, transforming, and publishing data.Data Governance Focused: You have solid experience in implementing data models ...