1 to 25 of 30 ETL Jobs in Manchester

Extensive experience in designing cloud data platforms using Azure, AWS, or exceptional on-premise design expertise. - At least 5 years in data engineering or business intelligence roles. - Proficiency in ETL and data pipeline design, with a technology-agnostic approach. - A solid understanding of data warehouse and data lake principles. - Expert SQL skills and demonstrable data modelling capabilities. About the Company More ❯

in most of the below areas... Experience in a Data Engineering (or similar) role Strong scripting skills in SQL (and Python would be a bonus) Experience designing and developing ETL/ELT processes using the Azure platform - Azure Synapse, Data Factory, Databricks or Fabric Knowledge of data lakes and medallion lake house design Working knowledge of Power BI or similar More ❯

dbt, AWS Glue, AWS Lake Formation, Apache Spark, Amazon Redshift) Strong understanding of data modeling, ELT design patterns, data governance, and security best practices Bonus . Experience with reverse ETL tools (e.g., Census) Knowledge of data privacy regulations (GDPR, ISO 27001) Experience supporting customer-facing analytics features in a multi-tenant SaaS environment Experience building data pipelines for AI and More ❯

enhance team efficiency and data quality. Skills & Experience Strong background in software development and technical leadership. Expertise in C#, .Net, SQL Server, SSIS, and SSAS. Experience in data integration, ETL development, and data warehouse environments. Previous exposure to financial or insurance systems highly desirable. Strong analytical and problem-solving skills with the ability to trace data flow and resolve issues. More ❯

design, delivery, and optimisation Contributing to major national infrastructure and security programmes with real impact What We’re Looking For Active DV clearance (essential) Strong background in data engineering, ETL, and data pipeline development Experience with AWS or Azure cloud technologies Excellent coding skills in Python, SQL, or Scala Understanding of data warehousing, modelling, and streaming technologies Confident working in More ❯

Python, C#, or similar languages. Experience with CI/CD pipelines, containerisation (Docker/Kubernetes) Familiarity with cloud platforms (Azure, AWS, or GCP) Understanding of data engineering principles, including ETL, data pipelines, and database management. Working knowledge of ML/AI concepts and technologies, including model deployment and monitoring. Strong problem-solving skills and the ability to work across disciplines More ❯

enhance team efficiency and data quality. Skills & Experience Strong background in software development and technical leadership. Expertise in C#, .Net, SQL Server, SSIS, and SSAS. Experience in data integration, ETL development, and data warehouse environments. Previous exposure to financial or insurance systems highly desirable. Strong analytical and problem-solving skills with the ability to trace data flow and resolve issues. More ❯

including interrogation of databases • Proficiency in T-SQL and working knowledge of SQL Server Management Studio • Experience with data governance, data quality, and metadata documentation • Understanding of relational databases, ETL/ELT processes, and APIs • Familiarity with GDPR and data protection regulations • A degree in a STEM subject or equivalent, plus relevant professional certifications • Experience working within the Housing or More ❯

. Solid experience with both SQL and NoSQL databases (Postgres, DynamoDB, etc.). Exposure to LLMs, embeddings, and vector search APIs . Strong understanding of data engineering , schema design, ETL, and optimisation. Proficiency with cloud (AWS preferred) and containerised deployments (Docker, ECS). Knowledge of secure coding practices and managing sensitive data. Excellent communication, problem-solving, and leadership skills. Nice More ❯

. Solid experience with both SQL and NoSQL databases (Postgres, DynamoDB, etc.). Exposure to LLMs, embeddings, and vector search APIs . Strong understanding of data engineering , schema design, ETL, and optimisation. Proficiency with cloud (AWS preferred) and containerised deployments (Docker, ECS). Knowledge of secure coding practices and managing sensitive data. Excellent communication, problem-solving, and leadership skills. Nice More ❯

. Solid experience with both SQL and NoSQL databases (Postgres, DynamoDB, etc.). Exposure to LLMs, embeddings, and vector search APIs . Strong understanding of data engineering , schema design, ETL, and optimisation. Proficiency with cloud (AWS preferred) and containerised deployments (Docker, ECS). Knowledge of secure coding practices and managing sensitive data. Excellent communication, problem-solving, and leadership skills. Nice More ❯

. Solid experience with both SQL and NoSQL databases (Postgres, DynamoDB, etc.). Exposure to LLMs, embeddings, and vector search APIs . Strong understanding of data engineering , schema design, ETL, and optimisation. Proficiency with cloud (AWS preferred) and containerised deployments (Docker, ECS). Knowledge of secure coding practices and managing sensitive data. Excellent communication, problem-solving, and leadership skills. Nice More ❯

. Solid experience with both SQL and NoSQL databases (Postgres, DynamoDB, etc.). Exposure to LLMs, embeddings, and vector search APIs . Strong understanding of data engineering , schema design, ETL, and optimisation. Proficiency with cloud (AWS preferred) and containerised deployments (Docker, ECS). Knowledge of secure coding practices and managing sensitive data. Excellent communication, problem-solving, and leadership skills. Nice More ❯

hoc data requests and provide technical expertise to stakeholders. Profile A successful Data Engineer should have: Proven experience with data engineering tools and technologies. Strong knowledge of database systems, ETL processes, and data modelling. Proficiency in programming languages such as Python, SQL, or similar. Experience with cloud-based data platforms and services. Ability to work collaboratively in a team environment More ❯

data platforms from on-premises data centres to public cloud environments (Azure preferred but not required). Deep knowledge of cloud services for data storage, data cataloguing/lineage, ETL processes, and data pipelines for ingestion, transformation, and delivery. Proficiency in Python and SQL for data processing, along with experience in implementing DevOps practices and an SRE mindset for continuous More ❯

data architecture, ensuring performance and scalability. Design, develop, and optimise SQL queries, stored procedures, and ETL pipelines. Work with AWS S3 data lakes and ERP systems to extract, transform, and load data. Ensure data accuracy and integrity across multiple sources. Integrate services via RESTful APIs and manage structured/unstructured data formats. Data Visualisation & Automation Build interactive dashboards in BI … Support forecasting and predictive analytics to guide strategic decisions. Translate complex data into clear, actionable recommendations. Required Skills & Experience Strong SQL expertise, including optimisation and performance tuning. Experience in ETL development, data modelling, and large datasets. Proficiency with BI tools such as Power BI, Superset, or Tableau. Experience with AWS data tools and governance. Strong analytical mindset with a focus More ❯

vision, data engineering including transformation and pipelines, data storage and architecture, or data governance. Previous consulting or professional services experience (or consulting-type roles) Understand data architecture concepts like ETL/ELT pipelines, data lakes/warehouses/lakehouses and data mesh and new emerging patterns Capabilities in one or more other specialist areas such as data architecture, data science More ❯

work with complex datasets. Technical knowledge in data models, database design, data mining, and segmentation preferred. Experience with reporting tools (e.g., Business Objects), databases (SQL), and programming (XML, JavaScript, ETL frameworks). Advanced Microsoft Excel skills, including formulas, pivot tables, and data manipulation. Experience with statistical analysis tools (Excel, SPSS, SAS, etc.). Familiarity with facilities management systems (e.g., Maximo More ❯

Data Engineer, you will have: Strong experience with SQL (e.g., MS SQL, Oracle). Knowledge of NoSQL technologies (e.g., MongoDB, InfluxDB, Neo4J). Experience with data exchange and processing (ETL, ESB, APIs). Proficiency in Python or similar programming languages. Familiarity with big data frameworks (e.g., Hadoop ecosystem). Desirable Skills: Understanding of NLP (Natural Language Processing) and OCR (Optical More ❯

data across multiple data types - text, images, and time-series (tabular) data. The Role You’ll join a small, collaborative data team in a Full stack Data Science role (ETL process through to building predictive models) working on live analytics, forecasting, and AI/ML projects. Key responsibilities include: Enriching and preparing datasets to uncover actionable insights Building and evaluating More ❯

C++,C#, NET, Java etc) (Essential) Experience of using configuration and version control tools (Rational ClearCase, Git) (Essential) Desirable Experience with database technologies (Oracle, SQL, etc) (Preferred) Knowledge of ETL toolsets (Pentaho etc) (Preferred) Understanding of middleware technologies (IBM MQ, RabbitMQ) (Preferred More ❯

C++,C#, NET, Java etc) (Essential) Experience of using configuration and version control tools (Rational ClearCase, Git) (Essential) Desirable Experience with database technologies (Oracle, SQL, etc) (Preferred) Knowledge of ETL toolsets (Pentaho etc) (Preferred) Understanding of middleware technologies (IBM MQ, RabbitMQ) (Preferred More ❯

Leading a team across engineering and integration - Work to ensure the data infrastructure of the business effectively supports analytics, AL, machine learning ML and reporting - Designing of data pipelines, ETL, ELT processes and architecture - Work with internal stakeholders and multiple 3rd parties to seamlessly integrate systems, platforms and applications To be considered suitable for this Data Engineering Manager role you … the following: - Team leadership and guidance - Data engineering and aligning of data to business needs - Cloud technologies (Azure/AWS) - Understanding of Agile methodology - Data warehousing and Data Lakes - ETL/ELT - DevOps understanding - API integrations More ❯

CD pipelines. Collaborate with AWS teams and internal stakeholders for pipeline scalability and optimization. Design and implement process improvements, including automation, data delivery optimization, and infrastructure re-design. Develop ETL pipelines and data workflows using AWS and SQL technologies. Partner with cross-functional teams (product, design, and leadership) to resolve technical issues and enhance platform capabilities. Build analytical tools and … Working knowledge of Python and SQL for automation and data pipeline development. Familiarity with monitoring and observability tools (Grafana, Prometheus, CloudWatch). Strong grasp of data architecture principles and ETL design patterns. Financial services or regulated industry experience (desirable). More ❯

ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication), use Redshift for efficient loading strategies and write ETL More ❯