data scientist

lead software engineer

platform engineer

senior data scientist

ai engineer

data platform engineer

Goldman Sachs

<div>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <strong>
  The Opportunity
  <br/>
  <br/>
 </strong>
 Join a team building the data foundations that support the firm&rsquo;s AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well-governed and high-performing data use across the firm.
 <br/>
 <br/>
 At Goldman Sachs, engineering teams are positioned at the centre of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform.
 <br/>
 <br/>
 This is a delivery-focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision-making and emerging AI use cases , and may also help extend platform tooling where additional functionality is needed.
 <br/>
 <br/>
 <strong>
  Role Summary
  <br/>
  <br/>
 </strong>
 As a
 <strong>
  Data Engineer
 </strong>
 in the
 <strong>
  Lakehouse and AI Data Platform team,
 </strong>
 you will design, build, test and support data pipelines and curated datasets on the firm&rsquo;s modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose. Where there are gaps in platform functionality, you may also contribute to shared tooling or framework components that improve how the platform is used and operated.
 <br/>
 <br/>
 The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Pipeline Engineering
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform.
  </li>
  <li>
   Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability.
  </li>
  <li>
   Where needed, build reusable tooling to improve delivery, consistency and operational support.
  </li>
  <li>
   Ensure data pipelines are production-ready, well tested and operationally supportable.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Data Modelling and Curation
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop raw, refined and curated datasets that support analytics, reporting and AI use cases.
  </li>
  <li>
   Apply sound data modelling principles to represent business entities, relationships and historical change accurately.
  </li>
  <li>
   Work with consumers to shape data products that are usable, well documented and aligned to business needs.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Data Quality and Reconciliation
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets.
  </li>
  <li>
   Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise.
  </li>
  <li>
   Contribute to clear standards for testing, monitoring and issue resolution.
  </li>
  <li>
   Contribute to practical improvements in testing, monitoring or reconciliation tooling where these strengthen platform reliability and day-to-day delivery.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Delivery and Partnership
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations.
  </li>
  <li>
   Communicate clearly on progress, risks, dependencies and design choices, including where delivery would benefit from improvements to shared platform tooling.
  </li>
  <li>
   For more senior candidates, take a broader role in technical leadership, task breakdown and support for junior engineers.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required
  <br/>
  <br/>
 </strong>
 <strong>
  Skills and Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s or master&rsquo;s degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise.
  </li>
  <li>
   Strong hands-on programming experience in Python or Java.
  </li>
  <li>
   Good working knowledge of SQL, including troubleshooting, optimisation and data analysis.
  </li>
  <li>
   Ability to learn new tools, internal platforms and delivery workflows quickly.
  </li>
  <li>
   Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Data Engineering Capability
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Understanding of temporal data modelling, including the handling of historical state and change over time.
  </li>
  <li>
   Knowledge of schema design, schema evolution and data compatibility considerations.
  </li>
  <li>
   Understanding of partitioning, clustering and other techniques used to improve data performance at scale.
  </li>
  <li>
   Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys.
  </li>
  <li>
   Practical approach to data quality, reconciliation and root-cause analysis.
  </li>
  <li>
   Experience building or supporting production data pipelines in a collaborative engineering environment.
  </li>
  <li>
   Experience working with distributed data processing frameworks such as Apache Spark.
  </li>
  <li>
   Working knowledge of common data formats such as JSON, Avro and Parquet.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  For More Experienced Candidates
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Stronger ownership of technical design across multiple datasets or pipeline domains.
  </li>
  <li>
   Experience guiding implementation standards, code quality and engineering practices within a team.
  </li>
  <li>
   Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Technology Environment
  <br/>
  <br/>
 </strong>
 The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies.
 <br/>
 <br/>
 <strong>
  Examples Of Technologies In Scope Include
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Data processing and logic: ANSI SQL, Apache Spark, Kafka
  </li>
  <li>
   Data formats: JSON, Avro, Parquet
  </li>
  <li>
   Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ
  </li>
  <li>
   Engineering and deployment: CI/CD tooling, containerised or Kubernetes-based deployment approaches where relevant
   <br/>
   <br/>
  </li>
 </ul>
 You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important.
 <br/>
 <br/>
 <strong>
  What We Are Looking For
  <br/>
  <br/>
 </strong>
 We are looking for engineers who can deliver well-structured, reliable solutions in production and who take ownership of the quality of what they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast-paced environment where data platforms support important business outcomes. It will also suit candidates who are willing to contribute to shared tooling or platform components that make the wider engineering environment more effective.
 <br/>
 <br/>
 <strong>
  Stronger Candidates Will Typically Demonstrate
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   sound judgement in technical trade-offs
  </li>
  <li>
   attention to detail in data correctness and testing
  </li>
  <li>
   a clear and structured approach to problem solving
  </li>
  <li>
   willingness to work closely with stakeholders and partner teams
  </li>
  <li>
   an ability to identify when delivery problems would be better solved through reusable tooling or platform improvements
  </li>
  <li>
   an interest in developing long-term expertise within the firm
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About Goldman Sachs
  <br/>
  <br/>
 </strong>
 At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.
 <br/>
 <br/>
 We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.
 <br/>
 <br/>
 We&rsquo;re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html
 <br/>
 <br/>
 &copy; The Goldman Sachs Group, Inc., 2026. All rights reserved.
 <br/>
 <br/>
 Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
</div>


Software Engineer - Data, Lakehouse and AI Data Platform Engineer - Analyst/Associate - London

monday.com

<div><p>linkAt monday.com, we help teams get more work done. We are the best AI work platform that empowers teams to automate, build, and scale their impact end-to-end with tools that actually execute the work for you. With over $1B in ARR, 250,000+ customers, and a global team, we&rsquo;re serious about building a product people love to use and giving our employees the same ownership and flexibility to shape the way the world works.</p><div></div><p><br>
We care about the impact you make, not the hours you clock, so we encourage initiative, ownership, and fresh thinking. We back our people with flexible work, wellness and mental health support, and a work environment built on collaboration.</p><div></div><p><br>
We are scaling our engineering teams in London and we are looking for experienced Software Engineers. This is an exciting opportunity to shape the future of our Engineering teams here! You'll drive the development of infrastructure features that shape our product's future from UI to database.</p><div></div><p><b><br>
You will join our Data group, which is building a groundbreaking new Data Platform, mondayDB 3.0. This next-generation system is designed to scale our product&rsquo;s capacity by orders of magnitude.</b></p><p>
Explore the future of monday with mondayDB.</p><p>
Dive deeper into the architecture of mondayDB 1.0</p><div></div><p><br>
Check out our Engineering Blog - https://engineering.monday.com/</p><div></div><p><b><br>
Please note this is a hybrid position of 3 days/week in our London office (Fitzrovia).</b><br>
<br>
<b>About The Role:</b></p><ul><li><p>
You'll work with experienced and highly talented engineers who are passionate about what they do, using cutting-edge technologies in a data- and impact-driven environment. We foster a culture of transparency, full ownership, teamwork, and a no-ego policy.</p><p>
Our engineering department consists of multiple groups, each responsible for a critical domain within the monday.com product. With over 350 engineers, we operate in cross-functional teams, collaboratively defining, improving, building, and delivering features.</p><p>
What you will do:</p><ul><li><p>
Play a key in shaping our product architecture and engineering excellence.</p></li><li><p>
Evolve our architecture and engineering practices to support the ever-growing scale of users, features, and data.</p></li><li><p>
Work alongside experienced and highly skilled developers in a CI/CD environment with cutting-edge technologies.</p></li><li><p>
Collaborate closely with Product and Design teams, taking full ownership and responsibility from conception to post-deployment in a fast-paced, dynamic environment.</p></li><li><p>
Tech stack: React.js, Redux, Node.js, Ruby on Rails, AWS, Elasticsearch, Redis, MySQL.</p></li></ul><p><i>
Note: Prior experience with our tech stack is not required; we welcome people willing to learn.</i><br>
<br>
<b>Requirments</b>:
</p></li><li><p>6+ years of experience as a Software Engineer.</p></li><li><p>
Strong technical expertise with a proven track record of building products that people love and use daily.</p></li><li><p>
Full-stack development experience, with a primary focus on backend.</p></li><li><p>
Experience developing large-scale, user-facing web products.</p></li><li><p>
Deep product understanding and a passion for creating software that delivers an exceptional user experience.</p></li><li><p>
Strong team player with excellent communication skills and empathy.</p></li><li><p>
Commitment to quality and simplicity in engineering and product development.</p></li></ul><p></p><p><b>
What </b><b>monday.com</b><b> can offer you:</b></p><ul><li><p>
Opportunity to join a well-funded, publicly listed company with big ambitions and strong growth potential.</p></li><li><p>
Competitive base salary, bonus, and RSUs.</p></li><li><p>
Private healthcare insurance, critical illness, and life insurance coverage.</p></li><li><p>
Pension contributions matched up to 7%.</p></li><li><p>
ClassPass membership.</p></li><li><p>
Buffet breakfast and lunch provided at the office, Monday to Thursday.</p></li><li><p>
Fully dedicated learning and development team that provides opportunities for our employees to hone and gain new skills.
</p></li><li><p>Fun team events, socials and offsites.</p></li><li><p>
Amazing company culture that values transparency and collaboration while never forgetting to have fun while we work! We've been named &quot;Best Place to Work&quot; in the UK.</p></li><li><p>
A global, dynamic and passionate environment with employees in Tel Aviv, New York, San Francisco, Miami, Chicago, Denver, London, Warsaw, Sydney, S&atilde;o Paulo, and Tokyo.</p></li></ul></div>

Senior Software Engineer - Data Platform

Moonpig

<div><div>We&rsquo;re the Moonpig Group &ndash; home to Moonpig, Greetz, Red Letter Days and Buyagift &ndash; and we&rsquo;re on a mission to make people feel loved, celebrated and remembered. Whether it&rsquo;s a card that gets them laughing out loud or a gift that makes their day, we help people stay close, no matter the miles.</div><div></div><div><br>
We&rsquo;re proud to be leading the online gifting revolution, with brilliant products, clever tech and a whole lot of heart. Our platform makes it easy to create moments that matter &ndash; packed with personal touches and delivered with care.</div><div></div><div><br>
We&rsquo;re not just about selling cards or gifts &ndash; we&rsquo;re here to spread joy, spark smiles and make every celebration feel extra special. And with values that guide how we work and support one another, we&rsquo;ve built a place where people (and ideas) can truly thrive.</div><div></div><div><br>
If you&rsquo;re looking to make an impact, bring your spark and be part of something meaningful &ndash; we&rsquo;d love to have you on the team. \uD83C\uDF19\uD83D\uDC37</div><br>
<div></div>
<h3 class="jobSectionHeader"><b>
About the Role</b></h3><div>
<p>
We're looking for an MLOps Engineer to join Moonpig's Data Platform team. In this role, you'll help build and scale the infrastructure that powers machine learning across the business. Working closely with data scientists, data engineers, software engineers, and stakeholders, you'll streamline the end-to-end machine learning lifecycle&mdash;from experimentation and model development through to deployment, monitoring, and continuous improvement.</p>
<div>
<div><div><p>As part of the ML Ops team, you'll play a key role in enabling innovation, personalisation, and data-driven decision-making across Moonpig. This is an opportunity to work with modern cloud technologies, shape scalable ML platforms, and make a direct impact on how machine learning is delivered in production.</p>
</div>
</div></div></div><h3 class="jobSectionHeader"><b>Key Responsibilities</b></h3><div>
<ul><li>Evaluate, integrate, and implement MLOps tools and frameworks to improve the efficiency and reliability of machine learning operations.</li>
<li>Design, implement, and manage CI/CD pipelines for deploying machine learning models into production environments.</li>
<li>Build and maintain infrastructure supporting data pipelines, model training, and model serving using cloud-native technologies and infrastructure-as-code practices.</li>
<li>Optimise machine learning workflows for performance, scalability, resource utilisation, distributed processing, and GPU acceleration.</li>
<li>Implement monitoring solutions to track model performance, identify anomalies, and support automated retraining processes.</li>
<li>Develop automated workflows for model testing, validation, and deployment, integrating with CI/CD tooling.</li>
<li>Partner with data scientists, data engineers, and software engineers to streamline the journey from experimentation to production.</li>
<li>Ensure security best practices are followed, including access control, data privacy, and compliance requirements.</li>
<li>Contribute to the ongoing evolution of the data platform, identifying opportunities to improve productivity, reliability, and scalability.</li>
<li>Build strong relationships across teams and support the adoption of data and machine learning best practices.</li>
</ul></div><h3 class="jobSectionHeader"><b>About You</b></h3><div>
<div><div><ul><li>Strong experience writing clean, maintainable, and production-ready Python code.</li>
<li>Proven ability to build scalable applications, data workflows, and automated solutions.</li>
<li>Experience working with machine learning pipelines and platforms such as AWS SageMaker or similar technologies.</li>
<li>Strong understanding of cloud-native services and experience designing, deploying, and operating applications within AWS or comparable cloud environments.</li>
<li>Comfortable working in agile environments, balancing technical quality with pragmatic delivery.</li>
<li>Curiosity and enthusiasm for learning new technologies and improving engineering practices.</li>
<li>Ability to collaborate effectively with a range of technical and non-technical stakeholders.</li>
<li>Strong problem-solving skills and a focus on building reliable, scalable solutions.</li>
</ul></div></div></div><h3 class="jobSectionHeader"><b>Our Tech Environment</b></h3><div>
<div><div><div><ul><li>MLOps: Snowflake, SQL, Python, FastAPI, Metaplane, Grafana, GitHub Workflows.</li>
<li>Infrastructure: AWS (SageMaker, ECS, Lambda, Glue, S3), Terraform, API Gateway.</li>
<li>Collaboration: GitHub, Jira, Confluence.</li>
</ul>
<p>We don't expect you to have experience with every technology listed above. We're interested in engineers who are excited to learn, collaborate, and help us build scalable machine learning platforms that support the future of Moonpig.</p>
</div>
</div></div></div><h3 class="jobSectionHeader"><b>How We Get There</b></h3><div>
<div>
<div><div><p>At Moonpig, we believe great products are built by great teams. You'll work in a collaborative environment where learning is encouraged, ideas are welcomed, and engineering excellence matters. We value people who are curious, supportive, and motivated to make a meaningful impact through technology.</p>
<p><b>
Interview Process</b></p>
<ul>
<li>Stage 1: Recruiter Screening Call</li>
<li>Stage 2: Hiring Manager Interview</li>
<li>Stage 3: Technical Assessment Interview with Two Team Members</li>
<li>Offer! \uD83C\uDF89</li>
</ul>
<p>Our process may vary depending on role and availability. We keep candidates informed of any changes.</p>
</div>
</div></div></div><div><b>What's in it for you?</b></div><div></div><div><br>
We believe in empowering our team to do their best work. Enjoy:</div><div>
\uD83D\uDCB0 Competitive Pay &amp; Bonuses: Plus, generous pension plans &amp; staff discounts.</div><div>
\uD83D\uDC86\uD83C\uDFFD Wellbeing First: Private healthcare (UK), mental health support &amp; dog-friendly offices (London &amp; NL).</div><div>
\uD83C\uDFD6️ Flexible Working &amp; Time Off: Generous holidays, hybrid working (1-3 days in office, depending on role/team) &amp; up to 20 days of international working.</div><div>
\uD83D\uDCC8 Career Growth: Learning allowances, coaching &amp; development programs.</div><div></div><div><b><br>
Want to know more?</b></div><div>
Explore our full benefits package: here</div><div>
Check out our podcast, tech blog and product blog to hear more about how we work and what we're building!</div><div></div><div><b><br>
Our Ways of Working:</b></div><div>
We trust our colleagues to do what&rsquo;s right and offer flexibility to support a balance between work and life. At the same time, face-to-face office time is an important and expected part of working at Moonpig Group. We believe regular in-person working supports collaboration, alignment, and effective decision-making. Candidates will have regular and ongoing time working from the office as part of their role, which will be discussed during the recruitment process.</div><div></div><div><b><br>
Moonpig Group's Commitment to Equality, Diversity, and Inclusivity:</b></div><div>
At Moonpig Group, we&rsquo;re all about creating a workplace where everyone feels they truly belong. We celebrate what makes each of us unique, whether that&rsquo;s our background, how we work best, or what matters most to us.</div><div></div><div><br>
From working parents who need flexible hours to neurodiverse colleagues with specific working styles, we&rsquo;re here to support our people in ways that work for them. Because when you feel valued and included, you can thrive, and so can we.</div><div></div><div><br>
We&rsquo;re proud to have a number of employee-led groups driving this forward, including our LGBTQ+, Gender Balance, Neurodiversity and EMBRACE (Educating Myself for Better Racial Awareness and Cultural Enrichment) communities, plus our Group-wide EDI committee. These teams help make sure every voice is heard and every idea has a place.</div><div></div><div><br>
We know that diversity fuels creativity, innovation and connection, and that&rsquo;s why we&rsquo;ll keep pushing for progress. Together, we&rsquo;re building a culture where everyone feels safe, supported, and free to be their brilliant, authentic selves.</div><div></div><div><br>
If you have a preferred name, please use it to apply and share your pronouns if you are comfortable to do so\uD83D\uDE0A - If you have any reasonable adjustment requests throughout the interview process please let us know on your application or speak to the Recruiter.</div><div></div><p><br>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</p></div>

ML Ops Engineer

Capgemini

<div><div><div><div><p><b>About the Job you are considering:</b></p>
<p>We are looking for an experienced AWS Databricks Engineer with strong hands-on expertise in Databricks, AWS cloud services, PySpark, Spark SQL, Delta Lake, Python, SQL, and data engineering. The candidate will be responsible for designing, developing, optimizing, and supporting scalable data pipelines and Lakehouse solutions for a banking client.</p>
<p>The ideal candidate should have strong experience in building enterprise-grade data platforms, processing large volumes of structured and semi-structured data, and implementing secure, reliable, and high-performance data pipelines in AWS-based environments.</p>
<p><b>Hybrid working:</b></p>
<p>The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.</p>
<p><b>Your Role:</b></p>
<ul><li>Define end-to-end data architecture for Azure-based data platforms using Azure Databricks, Azure Data Factory, ADLS Gen2, Delta Lake, Azure Synapse, and Power BI.</li>
<li>Design scalable and secure lakehouse architecture using bronze, silver, and gold data layers.</li>
<li>Lead architecture and design for data ingestion, transformation, curation, data marts, reporting, and analytics solutions.</li>
<li>Create high-level and low-level data architecture documents, data flow diagrams, integration architecture, and data platform blueprints.</li>
<li>Define architecture patterns for batch, incremental, real-time, and API-based data ingestion.</li>
<li>Design reusable data ingestion and transformation frameworks using ADF and Databricks.</li>
<li>Define data models for London Market Insurance data including policy, claims, premium, broker, bordereaux, delegated authority, reinsurance, exposure, and regulatory reporting data.</li>
<li>Work with business analysts and insurance SMEs to understand London Market business processes and translate requirements into data architecture.</li>
<li>Define standards for data modelling, source-to-target mapping, data quality, reconciliation, metadata, lineage, and auditability.</li>
<li>Design data governance, security, access control, and compliance frameworks for insurance data.</li>
<li>Support cloud migration, data warehouse modernisation, reporting transformation, and legacy system decommissioning initiatives.</li>
<li>Review technical designs, data models, ETL/ELT pipelines, and engineering implementation.</li>
<li>Provide architectural guidance to data engineers working on Azure Databricks, ADF, PySpark, SQL, and Delta Lake.</li>
<li>Collaborate with enterprise architecture, solution architecture, security, infrastructure, DevOps, and business teams.</li>
<li>Define CI/CD, DevOps, deployment, monitoring, and operational support architecture for data platforms.</li>
<li>Identify performance, scalability, reliability, and cost optimisation opportunities across Azure data services.</li>
<li>Support governance forums, architecture review boards, design authority meetings, and client stakeholder workshops.</li>
</ul><p><b>Your Skills:</b></p>
<ul><li>Strong hands-on experience with Databricks on AWS.</li>
<li>Strong experience with Apache Spark / PySpark.</li>
<li>Excellent programming skills in Python.</li>
<li>Strong SQL skills including complex queries, joins, CTEs, window functions, and query optimization.</li>
<li>AWS Secrets Manager &ndash; Secure secrets and credential management.</li>
<li>Amazon CloudWatch &ndash; Monitoring, logging, and alerting.</li>
<li>AWS Step Functions &ndash; Workflow orchestration, if applicable.</li>
<li>Amazon RDS / Aurora / Redshift &ndash; Source or target databases, where applicable.</li>
<li>Develop and maintain Databricks notebooks, workflows, jobs, and libraries.</li>
<li>Build reusable PySpark frameworks for ingestion, transformation, and data validation.</li>
<li>Implement Delta Lake features such as ACID transactions, schema evolution, time travel, and optimized storage.</li>
<li>Design and implement bronze, silver, and gold layers using medallion architecture.</li>
<li>Tune Databricks clusters for performance and cost optimization.</li>
<li>Monitor Databricks jobs and handle failures, retries, alerts, and job dependencies.</li>
<li>Implement job orchestration using Databricks Workflows, Airflow, AWS Step Functions, or similar tools.</li>
<li>Manage secrets, environment variables, and secure connections.</li>
<li>Support migration from legacy Hadoop/Spark platforms to Databricks on AWS, if required.</li>
</ul><p><b>'We are a Disability Confident Employer:</b></p>
<p>Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government&rsquo;s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:</p>
<ul><li>Declare they have a disability, and</li>
<li>Meet the minimum essential criteria for the role.</li>
</ul><p>Please opt in during the application process.</p>
<p><b>Make It Real (what does it mean for you):</b></p>
<ul><li>You&rsquo;d be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions.</li>
<li>To help support wellbeing we have trained &lsquo;Mental Health Champions&rsquo; across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.</li>
<li>You will be empowered to explore, innovate, and progress. You will benefit from Capgemini&rsquo;s &lsquo;learning for life&rsquo; mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.</li>
<li>You will be joining one of the World&rsquo;s Most Ethical Companies&reg;, as recognised by Ethisphere&reg; for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.</li>
</ul><p><b>Why you should consider Capgemini:</b></p>
<p>Growing clients&rsquo; businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you&rsquo;ll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what&rsquo;s possible. It&rsquo;s why, together, we seek out opportunities that will transform the world&rsquo;s leading businesses, and it&rsquo;s how you&rsquo;ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you&rsquo;ll build the skills you want. You&rsquo;ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.</p>
<p><b>About Capgemini:</b></p>
<p>Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of &euro;22.1 billion.</p>
<p><b>Make it real | www.capgemini.com</b></p>
<div><div><div><h2 class="jobSectionHeader"><b>Job Description</b></h2>
</div><div>The role is responsible for creating visual representations of data, concepts, ideas, or designs to facilitate understanding, communication, and decision-making. The work also involves translating complex information into visual formats that are clear, engaging, and impactful.</div>
</div><div><div><h2 class="jobSectionHeader"><b>Job Description - Grade Specific</b></h2>
</div><div>The role leverages their expertise in visual communication and data visualization to help clients make informed decisions, enhance their data driven storytelling, and improve their overall visual communication strategies.</div></div></div></div></div></div></div>

AWS Databricks Engineer

duvo.ai

<div>
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  About The Role
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 We already collect a lot of data &mdash; now we need someone to turn it into leverage. This is not a classic pipelines-and-warehouse hire (that's table stakes). It's an AI-native take on the data role: build the foundations, then build the agents and internal workflows on top that make the whole organization faster and more data-driven.
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 What you'll own
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 The data foundation &mdash; pipelines, warehouse, the substrate. Necessary, but not the point.
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 Agents and internal workflows built on top of that foundation &mdash; the actual leverage.
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 Enabling the org (product and beyond) to make faster, data-driven decisions.
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 This is an AI-native, senior role for someone who builds. You'll work across the data substrate and the agentic layer on top of it, and you'll be measured by how much faster and smarter you make the rest of the team.
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 Compensation Range: &euro;135K - &euro;190K
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</div>


Data Engineer (EU/UK Based - Remote)

Burns Sheehan

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  <strong>
   Senior Backend Engineer &ndash; Fintech - Python
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  <strong>
   📍 London (Hybrid, 3 days per week)
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  <strong>
   💵 &pound;80,000 &ndash; &pound;90,000 + 10-20% Bonus
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  <strong>
   💻 Python, Django, Flask, Pandas, APIs, Airflow, Data Processing
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  <strong>
   📈 Growing Private Credit technology platform
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  <strong>
   ⚙️ Backend ownership, platform engineering and data-adjacent challenges
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  We're partnered with a specialist technology business operating within the Private Credit and Asset Finance space. Following multiple new client wins and a significant increase in platform demand, they're expanding their engineering team with the hire of a Senior Backend Engineer.
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  This is a genuine ownership role within a small, highly capable engineering team. Engineers are responsible for features and components from design through to delivery, working closely with technical leadership and domain experts to shape the future of the platform.
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  The business has built a sophisticated software platform used to manage and monitor complex financial workflows. As new projects continue to onboard, they're looking for an experienced Python engineer to help scale backend services, APIs and data-processing capabilities across the platform.
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  <br/>
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  One of the more interesting aspects of the opportunity is the level of influence available. There is no traditional product management layer, meaning engineers have direct input into technical decisions, ownership of meaningful components and the opportunity to shape how the platform evolves.
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  <strong>
   Ideal profile:
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  &bull; 5+ years' commercial software engineering experience
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  &bull; Strong Python backend development experience
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  &bull; Commercial experience with Django, Flask or similar frameworks
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  &bull; Experience building APIs and backend services in production environments
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  &bull; Comfortable working with data-processing workflows, ETL pipelines or DataFrame-style tooling
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  <br/>
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  <strong>
   Senior Backend Engineer &ndash; Fintech - Python
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</div>


Senior Software Engineer

Signify Technology

<div>
 <strong>
  Job Title:
 </strong>
 Platform Engineer
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  Location
 </strong>
 : London (Hybrid)
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  Employment Type
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 : Full-time
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 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 My client are seeking an experienced platform engineer to join their team in London. This role is ideal for someone who thrives at the intersection of infrastructure, security, and software engineering. You&rsquo;ll be instrumental in designing, building, and maintaining our platform infrastructure, with a focus on secure, scalable, and reliable systems.
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  Key Responsibilities
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  <li>
   Lead infrastructure projects from start to finish, delivering secure, scalable, and high-performance systems
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   Design, build, and maintain cloud and on-premises infrastructure with security and reliability in mind
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   Write high-quality internal tools and automation scripts using Python
  </li>
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   Collaborate with engineering and security teams to ensure compliance, observability, and incident readiness
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   Contribute to infrastructure as code and CI/CD pipeline improvements
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   Monitor system health and performance, proposing and implementing enhancements
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  Requirements
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   5+ years of experience in platform, infrastructure, or DevOps engineering roles
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   Proven track record of leading infrastructure or security projects end to end
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   Strong knowledge coding in Python and comfortable using it
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   Strong background in infrastructure architecture and operations
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   Deep understanding of security best practices across cloud and on-prem environments
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   Proficiency in Python, with experience building tools or automation scripts
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   Familiarity with AWS and its tools
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  <li>
   Excellent communication skills and a collaborative mindset
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  </li>
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  Nice To Have
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 Experience with AI/ML infrastructure or supporting data science workflows
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 Exposure to MLOps tooling or machine learning model deployment
</div>


Platform Engineer

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