Implementation Engineer/ ETL

London
1 week ago
Create job alert

Implementation Engineer
Outside IR35
Remote
£400-£500
3 Months Initially
 
We are seeking an Implementation Engineer who possesses a strong foundation in data and business analysis. This role requires logical thinking and the ability to understand and interpret data. The ideal candidate will have experience configuring tools and platforms, with an understanding of scripts and plugins, rather than extensive coding expertise.
 
In this role, you will work primarily with the clients platform, which utilises ETL packages. A solid understanding of data analysis will significantly benefit your performance in this position.
 
Key Responsibilities:

Collaborate with clients to analyse data-driven business processes in detail, ensuring a clear understanding of the data and its implications. Document findings to prepare for implementation
Configure, extend, deploy, test, and validate complete solutions for our customers from end to end.
Conduct data analysis, exploration, testing, and validation while interacting with clients to comprehend data structures and use cases.
Configure connectors for various platforms such as Shopify, Akeneo, Bloomreach, and Optimove.
Set up workflows and data transformations.
Configure functions and transforms, including writing new plugins as needed.
Work with canonical data models (XDM) and perform data mapping using the clients portal, Jsonata, or code plugins.
Establish data hubs, focusing on data mapping and domain-specific components.
Create and manage data quality dashboards.
Develop data pipelines and manage warehouse/lake tables and views using Databricks and other tools, adhering to the medaillon architecture.
Configure, extend, or create BI dashboards with PowerBI that leverage data layers.
Perform testing and validation of implemented solutions.
Produce comprehensive documentation and training guides on the packages and their usage.
Provide guidance on the best approaches to leverage the platform to achieve desired results

Related Jobs

View all jobs

Lead Data Engineer

Data Engineer

Lead Data Engineer

Data Platform Engineer

Azure Data Manager

Senior Data Analyst

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Engineering vs. Data Science vs. Data Analytics Jobs: Which Path Should You Choose?

In the modern data-driven era, businesses in every sector—retail, finance, healthcare, and beyond—are constantly gathering large volumes of information to power insights and fuel decision-making. Consequently, the demand for data professionals has skyrocketed, with Data Engineering jobs in particular experiencing rapid growth. However, many job seekers remain unsure about how Data Engineering differs from Data Science or Data Analytics, or which role aligns best with their interests and career aspirations. This comprehensive guide will demystify the key differences among Data Engineering, Data Science, and Data Analytics. We’ll explore overlapping and distinctive skills, delve into typical job responsibilities, discuss salary ranges, and provide real-world examples of each role in action. By the end, you’ll have a clearer understanding of which path might suit you best. And when you’re ready to move forward, visit www.dataengineeringjobs.co.uk to explore the latest vacancies and take the next step in your data-focused career.

Data Engineering Programming Languages for Job Seekers: Which Should You Learn First to Launch Your Career?

In an era where data is fueling decision-making and driving innovation across industries, data engineering has emerged as a pivotal career path. Rather than just collecting and storing information, data engineers design and maintain sophisticated pipelines that transport, transform, and store massive datasets—enabling data scientists, analysts, and business teams to glean meaningful insights. If you’re researching opportunities on www.dataengineering.co.uk, you may be wondering: “Which programming language should I learn first for a career in data engineering?” It’s a great question. Data engineering spans a wide range of tasks—ETL pipelines, real-time streaming, data warehousing, big data frameworks, and more—requiring a versatile toolset. Languages like SQL, Python, Scala, Java, Go, and R each play unique roles in building robust data infrastructures. In this guide, you’ll discover: Detailed overviews of the top programming languages in data engineering. Pros, cons, and industry relevance for each language. A simple beginner’s project to sharpen your data engineering skills. Essential resources and tips to help you thrive in the job market.

UK Visa & Work Permits Explained: Your Essential Guide for International Data Engineering Talent

Data engineering has become a foundational pillar for organisations seeking to leverage their data assets effectively. From building robust data pipelines and integrating real-time analytics to migrating entire infrastructures to the cloud, skilled data engineers drive innovation and growth. In the United Kingdom, demand for data engineering professionals spans multiple sectors, including finance, healthcare, retail, tech start-ups, and government services. However, if you’re an international data engineering specialist looking to build or advance your career in the UK, one critical step stands before you: navigating the visa and work permit landscape. This comprehensive guide breaks down key visa routes, eligibility criteria, and practical steps to help you secure employment and settle into the UK’s thriving data ecosystem. Whether you specialise in ETL processes, big data platforms, or cloud infrastructure, understanding the UK visa system is the first step toward realising your ambitions.