Data Architect London, England, United Kingdom

Amach
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Staff Data Engineer

Data Analyst Team Lead

Senior Data Engineer (AWS, Airflow, Python)

AI Platform Engineer (DevOps / MLOps Focus)

Snowflake Data Engineer

Data Analyst

Join one of the world’s fastest growing technical teams We understand that looking for a new role can be a bit of a roller coaster, and at Amach we pride ourselves on providing a personal feel to the process, really getting to know our candidates.

Read on to find out what you will need to succeed in this position, including skills, qualifications, and experience.Amach is an industry-leading technology driven company with headquarters located in Dublin and remote teams in UK and Europe.Our blended teams of local and nearshore talent are optimised to deliver high quality and collaborative solutions.Established in 2013, we specialise in cloud migration and development, digital transformation including agile software development, DevOps, automation, data and machine learning.We are looking for a highly experienced Senior Data Engineer to design and implement cutting-edge cloud data solutions for our customer. The ideal candidate will have strong expertise in AWS Data Tools, SQLMesh, Terraform, Snowflake and Tableau, alongside a proven ability to design scalable data infrastructures that support advanced analytics and reporting. You will provide technical leadership, guide the engineering team and collaborate with stakeholders to ensure data strategies align with long-term business objectives. Strong skills in data security, Agile methodologies, and translating complex technical concepts into business language are essential for success in this role.Please note the successful candidate is expected to work from our customer's office in Warrington from time to time.Required skills:Experience in designing and implementing leading edge on premise and in Cloud data solutionsExperience working closely with the client and the delivery team to develop strategies and roadmaps that deliver client needs and requirementsDesigning architecture solutions that are in line with long-term business objectivesExperience around data securityExcellent knowledge of AWS Data Tools, SQLMesh, Terraform, Snowflake and TableauDesigning a data infrastructure that supports complex data analytics, reporting and visualisation servicesProviding technical leadership and direction to the engineering teamsBuilding effective relationships with senior technical staff so that there is a common understanding of goals and challengesMeeting with clients or executive team members to engage in architectural and requirement analysis discussionsCreating documentation and diagrams that show key data entities and creating an inventory of the data needed to implement solutionsHelping to maintain the integrity and security of data assetsRelevant 3rd level qualification with a strong technical focusExcellent knowledge and proven experience of working with IT Software Development Lifecycle methodologies with particular focus on Agile as the de facto methodologyExperience working with Agile teamsExperience in working with third party suppliers in the delivery of business or IT change initiatives – including experience of working with remote and co-located teams and vendorsExperience leading projects based on legacy technologies in an organisationA strong understanding of best practices, tools and techniques for delivery management with ability to continuously improve these processes in an agile delivery organisationAbility to translate technical to business speak and sometimes vice versaAssembling large, complex sets of data that meet non-functional and functional business requirementsIdentifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimising data delivery and automating manual processesTranslating business requirements into technical specifications, including data streams, integrations, transformations, databases and data warehousesDefining the data architecture framework, standards and principles, including modelling, metadata, security, reference data and master dataDefining reference architecture, which is a pattern others can follow to create and improve data systemsDefining data flows, i.e., which parts of the organisation generate data, which require data to function, how data flows are managed and how data changes in transitionCollaborating and coordinating with multiple departments, stakeholders, partners and external vendorsExperience in large enterprise data warehouseAbility to build and optimise data sets, ‘big data’ pipelines and architecturesAbility to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questionsExcellent analytic skills associated with working on unstructured datasetsAbility to build processes that support data transformation, workload management, data structures, dependency and metadataKnowledge of ODBC and JavaExperience with Data warehousing, Cubes and emerging EPP/MPP data designsExperience with Snowflake and AWS Data system preferableAWS Cloud Practitioner, Big Data Specialist, Tableau Professional or other similar certifications desiredAct as an influencer to help the existing team grow into modern modelling and reporting methodologiesData SecurityWhat’s in it for you:An opportunity to join a fast-growing companyOptions for career advancementLearning and development opportunitiesFlexible working environmentCompetitive rates based on experienceAt Amach, we strive to be an inclusive community of open-minded individuals with different backgrounds and we are committed to fostering, cultivating and preserving a culture of diversity, equity and inclusion. We strongly believe that a diversity of experience and background is essential to create a fulfilling environment and better solutions for our people and our customers. All Amach employees and contractors are expected to honour this policy and act to ensure that every individual is respected in the workplace.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.