machine learning engineer

ai engineer

data engineer

data scientist

software engineer

business intelligence engineer

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
We are looking for a highly analytical Business Intelligence Engineer to join Amazon&rsquo;s Global Accounting Business Intelligence and Analytics team.
 
 
The Accounting BI team supports the global Accounting organization with process automation/improvements, developing automated reporting solutions/tools, and improving the ability of the accounting organization to process, analyze, access and consume accurate and timely financial data. The team supports the global accounting organization and partners closely with accountants and financial analysts supporting the various businesses and industries Amazon operates in.
 
 
The ideal candidate thrives in a fast-paced environment, relishes working with ambiguity, big data, and enjoys the challenges of highly complex business context. This role requires an individual with excellent analytical abilities, deep knowledge of business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies.
 
 
Key job responsibilities 
<ul><li>Collaboration and partnership with Accounting and software development teams driving enterprise level projects</li><li>Contributing to the design, development, and maintenance of multiple scalable solutions supporting internal/external global stakeholders</li><li>Coordinating project prioritization with multiple stakeholders, managing and executing competing priorities from end to end within defined timelines</li><li>Supporting the global accounting organization with various ad-hoc reporting, analyses, and data processing needs</li><li>Integrating AI capabilities into business intelligence operations, identifying opportunities to leverage AI for enhanced insights, optimization, and operational efficiency</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.</li><li>Experience with data visualization using Tableau, Quicksight, or similar tools</li><li>Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)</li><li>Experience with SQL</li><li>Experience in the data/BI space</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Master's degree, or Advanced technical degree</li><li>Knowledge of data modeling and data pipeline design</li><li>Experience with statistical analysis, co-relation analysis</li></ul> 
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Business Intelligence Engineer, Accounting

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Own the analytics that leadership actually uses to run the business. As a Senior Business Intelligence Engineer, you'll define the metrics, build the data products, and deliver the analysis that directors and VPs depend on for high-stakes decisions where accuracy isn't negotiable. 
 
This is a senior role on a team that works closely with business leaders, so the problems you take on are ambiguous, consequential, and rarely solved by a standard report. You'll translate unclear business questions into precise, measurable analysis, build the data foundation to answer them, and defend your methodology when senior stakeholders press on it. We value depth and detail: clean logic, defensible metric definitions, and analysis that holds up under scrutiny. 
 
Why you'll want this role: 
 
<ul><li>A direct line of sight from your analysis to the decisions leadership makes</li><li>Hard problems with real stakes,</li><li>A team that cares about mechanisms, clarity, and getting definitions right</li><li>Room to set standards and grow into broader technical leadership</li></ul> 
Key job responsibilities 
What you'll do: 
 
<ul><li>Lead analytics on executive-level projects from the first question through to a clear recommendation</li><li>Build and own the pipelines, models, and dashboards that drive decisions, with reliability treated as part of the job</li><li>Set the standard for metric definitions, finance and operational reconciliation, and data quality across the team</li><li>Mentor other BIEs and raise the bar on SQL, data modeling, and analytical rigor</li><li>Present to senior leadership, demonstrating leadership principles: Ownership, and Have Backbone; Disagree &amp; Commit</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Experience programming to extract, transform and clean large (multi-TB) data sets</li><li>Experience with theory and practice of design of experiments and statistical analysis of results</li><li>Experience with AWS technologies</li><li>Experience in scripting for automation (e.g. Python) and advanced SQL skills.</li><li>Experience with theory and practice of information retrieval, data science, machine learning and data mining</li><li>Experience working directly with business stakeholders to translate between data and business needs</li><li>Experience with SQL</li><li>Experience with data visualization using Tableau, Quicksight, or similar tools</li><li>Experience in the data/BI space</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience managing, analyzing and communicating results to senior leadership</li></ul> 
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Senior Business Intelligence Engineer, EU Retail TCEE Data & Analytics

Cushman & Wakefield

<div>Job Title
Junior Analytics Engineer
Job Description Summary
Job Description
As a Junior Analytics Engineer within the EMEA Business Intelligence team, you will be an integral part of the Analytics Engineering pillar, contributing to the development and maintenance of the data foundation that powers BI delivery across EMEA. Working closely with senior Analytics Engineers, you will support the design and build of semantic models, curated datasets, and reusable data assets on our central data platform, gaining hands-on experience with enterprise-scale data modelling and platform engineering in a collaborative, high-performing team. You will work in close collaboration with the BI and Data Science &amp; Engineering teams, helping to lay the groundwork for data assets that increasingly support AI and agentic use cases alongside traditional BI delivery. You will start to develop an understanding of the business context behind the data you work with, helping to translate business needs into well-structured data assets and beginning to build the analytics translation skills that connect data and business outcomes. This is a role for someone who is technically curious, eager to learn, and motivated to build a strong foundation in analytics engineering. You will be guided and supported throughout, with clear opportunities to grow your skills, take on increasing responsibility, and develop toward a more senior role within the pillar.
Responsibilities:<ul><li>
Contribute to the design, build, and maintenance of semantic models and curated datasets on our central data platform, working under the guidance of senior Analytics Engineers.</li><li>
Support the standardisation of datasets, business logic, and data models to enable reusability and consistency across BI teams and markets.</li><li>
Assist with onboarding market-specific datasets onto our central data platform, collaborating with local stakeholders to understand data sources and requirements.</li><li>
Work closely with senior team members to ensure data assets meet the requirements of BI products being developed by the BI Development team.</li><li>
Develop a working understanding of the business context behind data requests, supporting senior team members in translating business needs into data structures and logic.</li><li>
Collaborate closely with Data Science &amp; Engineering colleagues, building familiarity with how data assets are used and shared across teams.</li><li>
Contribute to data quality checks and basic performance monitoring of data models and semantic layers, supporting senior team members in identifying improvements.</li><li>
Support early-stage work on building data foundations that can be used for AI and agentic use cases, such as preparing clean, well-structured datasets ready for future AI applications.</li><li>
Maintain clear documentation of data models, datasets, and platform assets, ensuring work is well-described and easy for others to understand and build on.</li><li>
Participate in peer reviews of data models and platform assets, incorporating feedback constructively to develop technical skills and maintain quality standards.</li><li>
Follow established best practices for data modelling, naming conventions, and platform governance, developing familiarity with the team's standards and ways of working.</li><li>
Engage actively in training, bootcamps, and mentoring programmes, taking ownership of personal development and building expertise in the tools and technologies used by the team.</li><li>
Support testing and quality assurance activities across project delivery, helping to ensure data assets and platform changes are reliable before release.</li></ul>
Requirements:<ul><li>
Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, Statistics, or a related technical discipline.</li><li>
Some practical experience with data engineering, analytics engineering, or BI development through employment, internships, or academic projects.</li><li>
Foundational understanding of SQL and a willingness to develop proficiency in building and optimising data models.</li><li>
Basic familiarity with data modelling concepts such as star schema or dimensional modelling; formal experience is an advantage but not required.</li><li>
Exposure to enterprise data platforms such as Databricks, Microsoft Fabric, Azure Synapse, or Snowflake is desirable.</li><li>
Awareness of Power BI or other BI tools and an interest in understanding how data assets underpin BI product development.</li><li>
Curiosity about AI, machine learning, and agentic technologies, and how data platforms are structured to support these use cases.</li><li>
An interest in understanding business needs and translating them into data and analytics solutions, with a willingness to develop commercial awareness alongside technical skills.</li><li>
Strong attention to detail and a methodical approach to building, testing, and documenting data assets.</li><li>
A collaborative and proactive mindset, with the eagerness to learn from senior team members and contribute to a high-performing team.</li><li>
Good communication skills, with the ability to ask clear questions and document work clearly.</li><li>
Knowledge of the real estate sector is a plus but not required.</li><li>
Fluent in English; additional European languages are an advantage.</li></ul> 
Cushman &amp; Wakefield is an equal opportunity / affirmative action employer. All qualified candidates will receive consideration for employment without regard to ethnicity, gender, gender identity or expression, sexual orientation, age, disability, religion, marital status, or any other legally protected characteristic. Cushman &amp; Wakefield is committed to equity in employment, and our goal is to have a diverse, inclusive and barrier-free workplace. If you are a person with a disability and need any other accessible accommodations during the hiring process, you are invited to bring this to the Talent Acquisition Advisor&rsquo;s attention once they have made contact. 

INCO: &ldquo;Cushman &amp; Wakefield&rdquo;</div>

Junior Analytics Engineer

Rippling

<div><h2 class="jobSectionHeader">About Rippling</h2>
Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system. 
Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365&mdash;all within 90 seconds. 
Based in San Francisco, CA, Rippling has raised $1.4B+ from the world&rsquo;s top investors&mdash;including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock&mdash;and was named one of America's best startup employers by Forbes. 
We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses. 
About the role
We are looking for a Compliance Governance Data Scientist to join our Compliance Risk Office (CRO). As Rippling expands rapidly into regulated markets globally (UK, EU, AU, SG, NZ), our compliance surface is outgrowing our legacy infrastructure. This role is a critical technical hire tasked with closing that gap. 
Moving beyond traditional Financial Crime/AML, you will build the technical data infrastructure to track cross-domain compliance risks across Complaints, Regulatory, Product Governance, and Employer of Record (EOR). You will own the automated aggregation of risk data, stand up our central Management Information (MI) reporting framework, and help launch our proprietary Compliance Risk App. 
The ideal candidate has 2&ndash;3 years of experience writing SQL, building dashboards, and translating qualitative compliance frameworks into quantitative data models. 
What you will do<ul><li>
Transition the CRO from manual data assembly to automated, real-time dashboards that provide a single consolidated view of risk for the Compliance Committee and Board.</li><li>
Serve as the functional data owner for the rollout of our Compliance Risk App, ensuring it serves as the single source of truth for all cross-domain risks.</li><li>
Work closely with our Governance Lead to translate the new compliance risk taxonomy into measurable Key Risk Indicators (KRIs) across all business units.</li><li>
Connect data pipelines from our Monitoring &amp; Testing (M&amp;T) domain programs directly to the central risk register so testing becomes completely risk-based.</li><li>
Run historical and predictive trend reporting on compliance issues, tracking open actions to ensure the business can actively evidence its compliance to global regulators.</li></ul> 
What you will need<ul><li>
2&ndash;3 years of experience as a Data Analyst, Risk Analyst, or Business Intelligence Engineer, ideally within a scaling Fintech, SaaS, or highly regulated operational environment.</li><li>
Strong proficiency in SQL (joins, CTEs, optimization) and experience building production-grade dashboards in BI tools (e.g., Tableau, Power BI, or Looker).</li><li>
Experience working with risk management platforms, GRC systems, or internal application development (experience with internal low-code/no-code internal app building is a massive plus).</li><li>
While you do not need to be a legal expert, you must be eager to learn cross-domain compliance areas like EOR regulations, marketing compliance, and global regulatory frameworks.</li><li>
Proven ability to operate in a fast-paced &quot;build&quot; environment, transforming unstructured, messy data into organized, automated pipelines.</li></ul></div>

Compliance Governance Data Scientist

Bauer Media Group

Location: London, Hybrid [1-2 days per week on site]
 
Our Team: How we enrich everyday life
 
You’ll be joining our Data & Decision Sciences (DDS) team at Bauer Media Audio, where we use data to power decisions across nine European markets. We’re a collaborative, cross-functional team working across commercial revenue, digital audiences, and consumer competitions, turning complex data into insights that shape how millions of people engage with our brands every day.
 
Working closely with Data Engineers, Data Scientists, Product Managers and business stakeholders, we combine central expertise with local market knowledge to deliver real impact.
 
The difference you will make
 
As an Analytics Engineer, you’ll play a key role in transforming raw data into trusted, business-ready insights. You’ll help build the data models and semantic layers that underpin reporting and analytics across Bauer Media Audio, enabling teams to make smarter, faster decisions.
 
This is an exciting opportunity to help modernise our data platform, working with emerging technologies and shaping how data is structured, defined, and consumed across the business.
 
Your role
 
You’ll design and build scalable data models and pipelines that translate complex data into meaningful insights for the business.
 
Responsibilities include, but are not limited to: 
Design and develop dimensional data models and marts using dbt and Kimball principles
 Build and maintain transformation pipelines from raw data to business-ready datasets
 Define and evolve semantic layers to ensure consistent metrics and reporting across tools like Looker, Power BI and Tableau
 Collaborate with Data Engineers to shape upstream data and improve data pipelines
 Implement data quality checks and maintain reliable, trusted datasets
 Support the migration and modernisation of legacy data platforms to Snowflake
 Maintain documentation including data dictionaries and semantic definitions
 Contribute to agile workflows, code reviews, and cross-functional collaboration
 Get involved with setting up Airflow DAGs or write Terraform to setup infrastructure.
 
The skills you will bring
 
Must-have: 
Strong SQL skills and experience with modern cloud data warehouses (e.g. Snowflake, Redshift, or BigQuery)
 Hands-on experience with dbt for data transformation and modelling
 Solid understanding of dimensional modelling (Kimball methodology)
 Experience working with BI tools such as Looker or Power BI
 Comfort working in agile teams using tools like Jira and GitHub
 Strong communication skills with the ability to translate data into business concepts
 
Nice-to-have: 
Experience with Snowflake or modern cloud data platforms
 Exposure to Airflow, Terraform, or CI/CD practices
 Experience with data quality tools such as Great Expectations
 Familiarity with Tableau or multi-BI environments
 Background in media, digital, or subscription-based businesses
 Experience using Python for data and analytics engineering tasks
 
About Bauer Media Group
 
We are a media business focused on creating content that matters to millions of people across Europe. Our offering extends from print and online publishing to audio broadcasting and entertainment, alongside investments in other media related sectors. With more than 500 million copies sold each year, we are one of Europe’s largest Publishers. From women’s and celebrities’ magazines to TV listings to food and special interest, we own some of the most popular publishing brands in Germany, UK, Poland and France – both digital and print. But not only that. Reaching over 61 million listeners weekly, we operate over 150 radio and podcast brands in nine countries, spanning the UK, Ireland, Poland, Slovakia, Denmark, Sweden, Finland, Norway and Portugal. Family-owned in the 5th generation, Bauer Media focuses on the long-term, with a consumer-first mindset that guides us across our diverse portfolio. Our workforce of 12,000 shares a common purpose: to deliver content and services that enrich people‘s everyday lives.
 
What’s in it for you
 
You’ll have 28 days holiday, bank holidays & 2 volunteer days to use.
 Your development matters, so access to our internal training provider – Bauer Academy, is a huge win.
 We have enhanced Maternity/Adoption, Paternity and Shared Parental Leave Pay.
 You’ll have the opportunity for flexible working.
 And much more! Find the full details of our benefits here
 
We are an international employer and equal opportunities are important to us. That's why we welcome everyone in their uniqueness, regardless of e.g. religion, gender, skin color, disability in our house.
 
We are committed to ensuring our recruitment process is inclusive and accessible to all. If you have a disability or a long term health condition, and need us to make any reasonable adjustments or do anything differently during any stage of the recruitment process, please let us know by emailing careershub@bauermedia.co.uk
 
We are actively recruiting for this position, so the job advert may close earlier than expected.
 
If you have any feedback regarding our UK recruitment process, please email careershub@bauermedia.co.uk we would love to hear from you.
 
Date Job Posting Last Updated: 25 Jun 2026
 
Location: 
London, GB, NW1 2PL
 
#job-location.job-location-inline { display: inline; }
 Req ID: 3719

Analytics Engineer

JD.COM

<div>
 
 JD.com (NASDAQ: JD and HKEX: 9618), also known as JINGDONG, has evolved from a pioneering e-commerce platform into a leading technology and service provider with supply chain at its core. Renowned for its supply chain innovation and excellence, the company has expanded into sectors including retail, technology, logistics, healthcare, and more, aiming to transform traditional business models with cutting-edge digital solutions. Know more about us: https://corporate.jd.com/
 
 
 
 
 
 We are looking for a Machine Learning Engineer who is passionate about turning machine learning and research into real, large-scale business impact to build a next-generation inventory prediction &amp; replenishment optimisation platform at Joybuy (https://www.joybuy.com/). Joybuy is JD.com&rsquo;s European full-category online retail brand designed to bring customers a faster, more convenient, and cost-effective shopping experience. Offering same-day and next-day delivery across the UK, Joybuy combines speed, reliability, and affordability to meet the needs of modern shoppers. As a Machine Learning Engineer focusing on demand forecasting, replenishment optimisation, and supply chain decision intelligence, you will design, develop, and deploy models that support billions of dollars ' worth of global inventory flow decisions. Your work directly influences forecast accuracy, stock availability, fulfilment cost, and customer experience.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Design, implement, and evaluate machine learning models for demand forecasting, replenishment, and fulfilment optimisation.
 </li>
 <li>
 Develop innovative algorithmic solutions to complex forecasting and supply chain problems in close collaboration with product, engineering, and operations teams.
 </li>
 <li>
 Contribute to the technical direction of the fulfilment intelligence platform and influence model architecture, system design, and best practices.
 </li>
 <li>
 Work onsite in London, UK.
 </li>
 </ul>
 
 
 
 
 
 Minimum Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Engineering, Computer Science, Mathematics, or a related technical field.
 </li>
 <li>
 3+ years of professional experience as a machine learning engineer or applied research scientist.
 </li>
 <li>
 Experience programming in Java, C++, Python or a related language
 </li>
 <li>
 Experience with neural deep learning methods and machine learning
 </li>
 <li>
 Demonstrated ability to work independently with minimal guidance; proactively manage tasks and priorities across multiple projects; analyze and execute work efficiently; collaborate effectively with cross-functional teams; and thrive in fast-paced, results-driven environments.
 </li>
 <li>
 Effective communication skills in English.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Professional experience in e-commerce, retail forecasting, fulfilment logistics, inventory planning, or similar domains.
 </li>
 <li>
 Hands-on experience with modelling tools such as Python, PyTorch, TensorFlow, scikit-learn etc.
 </li>
 <li>
 Hands-on experience building large-scale distributed machine learning systems such as Hadoop, Spark etc.
 </li>
 <li>
 Effective communication skills in Chinese.
 </li>
 </ul>
 
 
 
 
 JD.com is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
 
 
 
 
 
 JR101321
 
</div>

Machine Learning Engineer - Fulfilment

Forward Role Secure

<div>
 
 
 
 Data Engineer (National Security)
 
 
 
 
 
 
 
 
 
 
 
 Location
 
 : Opportunities across South West, North West and London National Security hubs
 
 
 
 
 
 
 Hybri
 
 d: typically 3&ndash;4 days per week highside, depending on programme
 
 
 
 
 
 
 Salary:
 
 &pound;70,000 &ndash; &pound;120,000 plus bonus and benefits, depending on experience and SFIA grading
 
 
 
 
 
 
 Clearance
 
 : Active National Security clearance preferred
 
 
 
 The Opportunity:
 
 If you're a Data Engineer operating within NS and looking for broader technical exposure, greater ownership and a genuinely strong engineering culture, this is worth a look...
 
 
 
 
 
 We're supporting a specialist engineering consultancy that is rapidly expanding its NS capability following a number of major programme wins and long-term growth plans.
 
 
 
 
 
 What stands out about this organisation isn't just the technology. It's the environment.
 
 
 
 
 
 The business has built a reputation as a genuinely people-first employer, recognised through Best Workplace awards, strong Glassdoor reviews and consistent investment in learning and development. Engineers are trusted to shape solutions, work closely with customers and continue developing their skills through dedicated training and support programmes.
 
 
 
 
 
 Many people join from larger organisations looking for less red tape, broader project exposure and the opportunity to have a more visible impact.
 
 
 With significant growth planned over the next 18 months, there is a genuine opportunity to help shape capability as the team scales.
 
 
 .
 
 
 
 The Role
 
 
 
 As a Data Engineer, you'll help build secure cloud-native data platforms supporting analytics, operational intelligence and AI-enabled capability across NS programmes.
 
 
 
 
 
 Typical responsibilities include:
 
 
 
 
 
 &bull; Building scalable data pipelines and ETL frameworks using Python and modern cloud-native engineering approaches
 
 
 &bull; Developing AWS-based data platforms supporting analytics, operational intelligence and AI-re
 
 
 ady services
 
 
 &bull; Working with large-scale operational, geospatial and miss
 
 
 ion datasets
 
 
 &bull; Supporting distributed data architectures and secure cloud transformation
 
 
 initiatives
 
 
 &bull; Collaborating directly with the customer to solve complex data challenges and influence technical direction
 
 
 &bull; Contributing to modern engineering practices across automation, testing, observability and platform reliability
 
 
 The exact technology stack varies between programmes, but typically includes AWS, Python, distributed processing technologies and modern data engineering tooling.
 
 
 
 
 
 The organisation values engineering mindset, curiosity and stakeholder engagement far more than matching every technology perfectly.
 
 
 
 
 
 This role is particularly suited to engineers who enjoy combining cloud, data and customer-facing problem solving rather than operating within a narrow technical silo.
 
 
 
 
 
 
 Security Requirements
 
 
 
 Due to the nature of the work, candidates should already be operating within National Security, with the ability to work highside.
 
 
 
 
 
 
 Why Apply?
 
 
 
 &bull; Best Workplace recognised culture
 
 
 &bull; Strong Glassdoor reviews and positive employee feedback
 
 
 &bull; Significant investment in learning and development
 
 
 &bull; Broad exposure across cloud, analytics, geospatial and AI-enabled capability
 
 
 &bull; Growing National Security practice with genuine progression opportunities
 
 
 &bull; Opportunity to influence solutions rather than simply deliver against a specification
 
</div>

Data Engineer (National Security)

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