1 to 25 of 35 Part-Time ETL Jobs in England

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

Snowflake, BigQuery, Redshift or similar. \n ● Experience with cloud-based data platforms, particularly AWS or GCP. ● Experience with data warehousing, data modelling, and ETL development. ● Strong analytical & communication skills and an understanding of what drives the performance of a product to reach the company's commercial goals. ● Hands-on experience ...

high‐performance data ingestion pipelines for batch and streaming data from multiple sources, including sensor, geospatial, communications and operational systems. \n Design and implement ETL/ELT workflows to transform, enrich and validate data for downstream analytics and machine learning use. \n Build scalable, distributed data processing solutions using modern ...

high‐performance data ingestion pipelines for batch and streaming data from multiple sources, including sensor, geospatial, communications and operational systems. \n Design and implement ETL/ELT workflows to transform, enrich and validate data for downstream analytics and machine learning use. \n Build scalable, distributed data processing solutions using modern ...

cloud data warehouse, data lake or data platform) to enable digital transformation \n\n \n Working with clients on data warehousing, building operational ETL/ELT data pipelines across a number of sources, and constructing relational and dimensional data models \n\n \n Performing maturity assessments across clients’ data capabilities ...

Familiarity with prompt engineering principles and LLM-based tools \n Effective communication skills to present data findings and support users \n Experience with ETL/ELT processes and architecture in data pipelines \n Experience building models for dashboard or cube consumption \n Familiarity with cloud-based data lake platforms such ...

Desirable: \n \n Experience working in government, defence, or highly regulated industries with knowledge of relevant standards. \n Experience with additional data processing and ETL tools like Apache Kafka, Spark, or Hadoop. \n Familiarity with containerization and orchestration tools such as Docker and Kubernetes. \n Experience with monitoring and alerting ...

BigQuery and big data technologies like Spark, Flink etc. \n Solid grasp of Kubernetes, CI/CD and Terraform. \n Working knowledge of ETL and ELT frameworks and orchestration tools like Airflow and dbt. \n Ability to provide clear input, guide, empower junior members of the team to achieve desired ...

and dataset is discoverable, addressable, and secure by design. \n Data capabilities: You understand the full lifecycle of data from data discovery, storage, pipelines, ETL, streaming through to how data is managed including data quality, metadata management and how data is used for applications and core decision making through advanced ...

Experience in resolving data quality issues and ensuring data accuracy through cleansing and standardisation techniques. \n Use of data integration tools: Skilled in using ETL tools for data integration and storage. Ensures data interoperability with other datasets. \n Collaboration with data professionals: Experience collaborating with other data professionals to improve ...

agreements \n Experience coordinating cross-functional stakeholders and contractor resources to maintain operational continuity and quality output \n Knowledge of data processing frameworks, including ETL pipelines, data integration, and data modeling (experience with Databricks or Spark preferred) \n Strong analytical and problem-solving skills with the ability to communicate clearly ...

design of solutions using one or more from: SQL and noSQL technologies, data streaming, logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies \n A thorough understanding of one or more from: Master Data Management, Data Lineage analysis, Metadata Management, Data Quality assessment and management ...

Dynamic 365 data model. \n Deep technical expertise in Data Engineering including In-depth knowledge of Data Engineering practices, including Data Storage, Data Visualization, ETL, Data Integration & Migration, Data Warehousing, and Business Intelligence. \n Strong communication skills with the ability to develop thought leadership materials, including whitepapers, blogs, webinars, etc. ...

Intelligence, Data Warehousing, Data Science, or Analytics Engineering). Conceptual and practical familiarity with modern cloud data platforms (Snowflake, AWS) and data pipelines (dbt, ETL/ELT workflows). \n Active curiosity and comfort leveraging Generative AI tools to streamline administrative and analytical outputs. \n Expert-level skills in Requirements ...

Experienced in Scrum/Kanban environments, participating in ceremonies (Dailies, Refinement, Retrospectives) and managing tasks via backlogs. \n Data Engineering Best Practices: Knowledge of ETL/ELT patterns, data versioning, and building robust, automated pipelines. You'll ensure data security and compliance requirements are met with solutions you propose and ...

metadata analysis, fields/entity, and data lineage, sql/no sql databases \n Experience with one of Azure/AWS/GCP \n ETL tools like Informatica, Alteryx and Business Glossary tools like Collibra, Azure Purview or Apache Atlas. \n TDD/BDD, Experience working in an Agile development ...

e.g., Azure) and big data technologies like Spark, Flink etc., \n Solid grasp of Kubernetes, CI/CD and Terraform \n Working knowledge of ETL and ELT frameworks and orchestration tools like Airflow \n Hiring, developing, and retaining cyber data platform talent \n Ability to deliver clear input, guide, empower ...

scale data processing solutions and deploying into a production environment \n • Proficient in SQL and SQL extensions for analytical queries \n • Solid understanding of ETL/ELT data processing pipelines and design patterns \n • Aware of key features and pitfalls of distributed data processing frameworks, data stores and data serialisation ...

solutions for the future state architecture \n Knowledge of some Data Management technologies such as Relational and Columnar Databases, and/or Data Integration (ETL) or API development. \n Knowledge of some Data Formats such as JSON, XML, and binary formats such as Avro or Google Protocol Buffers. \n Experience ...

enable self-service of data analytics to data hungry internal users as well as automation of all our data workflows - from simple ETL jobs to ML training and prediction. \n The data team at OEV is growing at speed. We have invested time and resources on establishing a core data ...

and managing the delivery of complex multi-team initiatives within a technical landscape bridging the gap between business strategy & engineering execution including: \n \n ETL/ELT & Data Pipeline knowledge \n Data Modelling & Architecture \n Data Quality & Governance \n Data observability \n Cloud data ecosystems \n\n\n Prior experience ...

proactive about improving documentation, governance, workflows, and system reliability \n\n Nice to have: \n \n Braze technical implementation experience \n Reverse ETL/activation tooling (e.g. Hightouch) \n API or integration engineering experience \n HTML/CSS/Liquid or templating familiarity \n\n Additional Information \n For everyone ...

analytics engineering, or related disciplines delivering enterprise data solutions \n Strong proficiency in Databricks, SQL, and Python/PySpark, including building, optimizing, and troubleshooting ETL pipelines \n Experience designing scalable, maintainable data architectures and dimensional models for BI, reporting, and analytical use cases \n Proven ability to partner with business … agreed definitions and business expectations \n Act as a trusted technical partner, balancing delivery speed, data quality, and long-term scalability \n Architect modular ETL pipelines to improve maintainability, reuse, and traceability \n Define and uphold engineering standards across coding, testing, documentation, and version control practices \n Support BI lakehouse ...

analytical skillset on a variety of internal and external data. Leads, instructs, and mentors newer Data Engineering crew. \n Core Responsibilities \n 1. Writes ETL (Extract/Transform/Load) processes, designs database systems and, develops tools for real-time and offline analytic processing. \n 2. Troubleshoots software and processes ...

ensure the products are adopted and trusted. \n\n To do that, it’s essential you bring the following: \n \n Experience using ETL tools to ingest, transform and store data. \n Experience designing and developing cloud data platforms (AWS, GCP or Azure preferable) \n Good knowledge of data warehouse ...