data engineer

data scientist

machine learning engineer

ai engineer

senior software engineer

data software engineer

Neal's Yard Remedies

Love SQL, DBT, ETL and WMS?
<br>Love an abbreviation?
<br>We do too!
<br>You'll be a tech wizard with previous experience within a Retail business. You'll loves data and can extract, formulate, and manipulate data to create insightful reports to tell the right stories and set business focus. You will be an enabler for Neals Yard Remedies, harnessing the power of technology to drive insight, innovation and impact. You'll help shape our future data landscape, building the infrastructure and tools to empower our teams to make bold data led decisions.
<br>With a laser focus on the reliability, stability and continuous improvement of our data and integration landscape, you'll support critical systems that underpin retail, distribution and operational processes. You'll maintaining and enhance data pipelines, integrations and platform capabilities that enable the business to operate effectively every day.
<br>Working across data engineering and systems integration, you'll help drive best practice, improve documentation, strengthen platform resilience and support the business through reliable, trusted data and connected systems.
<br>Forward thinking in your approach, you'll help design and deploy scalable data solutions to help unlock opportunities, aligned with our strategic objectives, including building ETL pipelines, whilst collaborating across departments to ensure data is easily accessible.
<br>You'll enjoy assisting teams in a true partnering capacity, comfortable challenging where necessary, using your excellent communication skills to effectively communicate technical information to non-technical personnel. You'll have the ability to directly influence and support commercial decision making.
<br>You'll join a fast paced and fun environment, where no two days are the same, playing a critical role in managing our data story and delivering real value. Our working culture has the perfect mix of responsibility and ownership, balanced with support and encouragement. You'll have freedom in this role to carve your own path, but with the safety net of a knowledgeable and supportive wider Technology Team.
<br><br>
We are open to applications from a Senior Data/ Software Engineer or someone ready to make the next step in their career. Passion for what you do is paramount, as we believe in you, to do what you do well, in our beautifully unique environment.
<br><br>
<b>What you'll have:</b><br>
Strong hands-on experience with Snowflake in a production environment
<br>Experience working with Netsuite and supporting ERP integrations, is an advantage
<br>Advanced SQL skills and experience developing data transformation solutions using dbt
<br>Experience working with Jitterbit or a comparable iPaaS integration platform
<br>Knowledge of Shopify integrations and eCommerce systems
<br>Strong understanding of FTP/SFTP protocols and file transfer configuration
<br>Experience supporting enterprise data and integration platforms in a live operational environment
<br>Experience working with EDI integrations and data exchange processes
<br>Understanding of warehouse management system (WMS) integrations would be beneficial
<br>Knowledge of JavaScript and HTML is desirable
<br><br>
<b>What you'll get:</b><br>
Generous employee discount
<br>Casual dress
<br>Company pension
<br>Long service benefits
<br>Paid community days
<br>25 days annual leave plus Bank Holidays
<br>Employee Assistance Programme

Senior Data / Software Engineer

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.</li>
<li>2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.</li>
<li>1 year of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.</li>
<li>1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul><li>
Master's degree or PhD in Computer Science or related technical fields.</li><li>
2 years of experience with data structures and algorithms.</li><li>
Experience with C++, Parallel Computing, Blender.</li><li>
Experience developing accessible technologies.</li><li>
Proficiency in Python and experience with frameworks for large-scale data processing.</li><li>
</li></ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first-party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.</div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)</li>
<li>Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.</li>
<li>Lead high-volume synthetic datasets including metadata deliveries for XR and Platform and Devices (P&amp;D) projects.</li>
<li>Build modular toolkits for GenAI bulk inference and metadata extraction.</li>
<li>Develop end-to-end pipelines for fine-tuning in-house foundational models.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Software Engineer III, GenAI Data Operations Research, XR

Speechify

<div><p>The mission of Speechify is to make sure that reading is never a barrier to learning.</p>
<p>
Over 50 million people use Speechify's text-to-speech products to turn whatever they're reading &ndash; PDFs, books, Google Docs, news articles, websites &ndash; into audio, so they can read faster, read more, and remember more. Speechify's text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.
</p><p>Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting &ndash; Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.</p>
<p><b>
Overview</b></p>
<p>
We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.</p>
<p><b>
What You'll Do</b></p>
<ul>
<li>Be scrappy to find new sources of audio data and bring it into our ingestion pipeline</li>
<li>Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.</li>
<li>Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.</li>
<li>Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team's dataset roadmap to power Speechify's next-generation consumer and enterprise products.</li>
</ul>
<p><b>An Ideal Candidate Should Have</b></p>
<ul>
<li>BS/MS/PhD in Computer Science or a related field.</li>
<li>5+ years of industry experience in software development.</li>
<li>Proficiency with bash/Python scripting in Linux environments</li>
<li>Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)</li>
<li>Experience with web crawlers, large-scale data processing workflows is a plus</li>
<li>Ability to handle multiple tasks and adapt to changing priorities.</li>
<li>Strong communication skills, both written and verbal.</li>
</ul>
<p><b>What we offer</b></p>
<ul>
<li>A fast-growing environment where you can help shape the company and product.</li>
<li>An entrepreneurial-minded team that supports risk, intuition, and hustle.</li>
<li>A hands-off management approach so you can focus and do your best work.</li>
<li>An opportunity to make a big impact in a transformative industry.</li>
<li>Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.</li>
<li>Opportunity to work on a life-changing product that millions of people use.</li>
<li>Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.</li>
<li>Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.</li>
</ul>
<p><b>Think you're a good fit for this job?</b></p>
<p>
Tell us more about yourself and why you're interested in the role when you apply.
<br>
And don't forget to include links to your portfolio and LinkedIn.</p>
<p><b>
Not looking but know someone who would make a great fit?</b></p>
<p>
Refer them!</p>
<p><b>
Speechify is committed to a diverse and inclusive workplace.</b></p>
<p>
Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.</p></div>

Software Engineer, Data Infrastructure & Acquisition - London, United Kingdom

Arrows

<div>
 <p>
  I'm currently partnered with a fast-growing InsureTech business that is evolving its internal data platform and looking to hire a Staff Data Engineer into a small, high-impact team.
 </p>
 <p>
  <br/>
 </p>
 <p>
  This is a broad and genuinely technical role sitting at the heart of the data function responsible for the design, build and maintenance of a cloud-based data platform that directly supports commercial decision-making across the business. You'd have real ownership from day one, working closely with analysts across Marketing, Product, Pricing and Underwriting to translate business needs into scalable, reliable data solutions.
 </p>
 <p>
  <br/>
 </p>
 <p>
  The environment suits someone who enjoys building and optimising data infrastructure, takes pride in data quality, and wants to be part of a platform that is actively evolving including a move to Google BigQuery starting in 2026.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What you'll be doing:
  </strong>
 </p>
 <ul>
  <li>
   Designing, developing and maintaining robust data pipelines and ETL/ELT processes
  </li>
  <li>
   Building and managing performant data models to support analytical capability across the business
  </li>
  <li>
   Leading performance monitoring, tuning and internal platform improvement initiatives
  </li>
  <li>
   Leveraging cloud-based infrastructure to build scalable, high-availability data solutions
  </li>
  <li>
   Collaborating closely with analysts and business stakeholders to turn data requirements into effective solutions
  </li>
  <li>
   Ensuring data quality and accuracy with rigour and consistency
  </li>
  <li>
   Mentoring and guiding junior data engineers, providing technical oversight and expertise
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Tech stack includes:
  </strong>
 </p>
 <p>
  SQL, dbt, Fivetran, Google Cloud Dataflow, BigQuery, Azure Data Factory, Databricks, GCP, Azure, Python, Git, Power BI / Tableau / Qlik.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What they're looking for:
  </strong>
 </p>
 <ul>
  <li>
   Advanced SQL proficiency including complex queries, indexing and optimisation
  </li>
  <li>
   Strong experience with ETL tooling and ELT processes
  </li>
  <li>
   Solid understanding of data warehousing and dimensional modelling
  </li>
  <li>
   Hands-on cloud experience across GCP, Azure or AWS
  </li>
  <li>
   Familiarity with version control and DevOps practices
  </li>
  <li>
   Python knowledge is beneficial but not essential
  </li>
  <li>
   Comfortable working in an agile, fast-paced environment
  </li>
 </ul>
 <p>
  <br/>
 </p>
</div>


GCP Staff Data 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

JPMorganChase

<div><b>JOB DESCRIPTION</b><br>
<br>
<br>
<p>Join us to shape the future of financial analytics and technology. You will lead impactful projects that drive advanced data engineering and AI solutions across global teams. We offer opportunities for career growth, collaboration, and technical excellence. Your expertise will help us deliver mission-critical systems and foster a culture of innovation. Be part of a team where your ideas and leadership make a difference.</p><p><br>
As a Lead Data Engineering &amp; AI Technical Initiatives in the Global Analytics team, you will guide technical direction and drive innovation in real-time data processing. You will collaborate with research and trading teams to deliver advanced analytics capabilities and support global business needs. Your role will focus on building robust tools, mentoring team members, and influencing product design. You will help shape our technical standards and foster a diverse, inclusive, and collaborative environment.</p><p><b>
Job Responsibilities:</b></p><ul><li>
Lead technical initiatives across global analytics teams, providing guidance and direction in a high-velocity environment.</li><li>
Design, build, and optimize real-time data processing pipelines and applications to ensure reliability and performance.</li><li>
Leverage AI technologies to enhance data engineering workflows and automate SDLC processes.</li><li>
Collaborate with research and trading teams to onboard new datasets efficiently and consistently.</li><li>
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.</li><li>
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.</li><li>
Build and support robust tools and frameworks for quantitative research and production trading.</li><li>
Mentor and develop team members, manage book of work, and drive continuous improvement in SDLC, testing, and coding standards.</li><li>
Influence product design, application functionality, and technical operations to meet evolving business demands.</li><li>
Serve as a subject matter expert in Python, KDB/Q, data engineering, and AI.</li><li>
Champion diversity, inclusion, and collaboration within global teams.</li></ul><p>
</p><p><b>Required Qualifications, Capabilities, and Skills:</b></p><ul><li>
Applied experience in software engineering, preferably in large-scale, fast-paced financial environments.</li><li>
Hands-on experience delivering system design, application development, testing, and operational stability for analytics-driven teams.</li><li>
Expertise in Python, KDB, or C++ for real-time data processing, application development, or data engineering.</li><li>
Working knowledge of AI technologies to support data engineering, analytics, or SDLC automation.</li><li>
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.</li><li>
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices</li><li>
Proficiency in automation and continuous delivery methods; advanced understanding of agile methodologies.</li><li>
Experience leading and mentoring teams in a global, collaborative environment.</li><li>
Ability to tackle complex design and functionality problems independently and drive solutions across distributed teams.</li><li>
Academic background in Computer Science, Computer Engineering, Mathematics, or a related technical field.</li></ul><p>
</p><p><b>Preferred Qualifications, Capabilities, and Skills:</b></p><ul><li>
Experience with market data venue and vendor data platforms.</li><li>
AWS experience; practical cloud native/cloud experience is a plus.</li><li>
Experience with Terraform and Kubernetes for managing production environments in public cloud.</li><li>
Knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading
</li></ul><b>ABOUT US</b>
<br>
<br>
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.<br>
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.<br>
</div></div><br>
<br>
<b>ABOUT THE TEAM</b>
<br>
<br>
J.P. Morgan's Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Lead Software Engineer - Python and kdb+ / AI data integration, Alt Data & Data Ingestion

Field

<div><h3 class="jobSectionHeader"><b>Description</b></h3><div><b><br>
Your Mission</b></div><div></div><div><br>
Field is an Energy Storage Provider that operates across the value chain from project development through to asset management and trading. At the heart of Field&rsquo;s operations and trading sits GAIA, our in-house automated energy trading platform which makes hundreds of decisions a day based on market signals, asset telemetry and forecasting model outputs. GAIA&rsquo;s success has led to its outputs being more deeply integrated into the wider business along with the tools and technologies that have driven its success.</div><div></div><div><br>
This is where you come in. The successful candidate will build and improve the data platform that powers GAIA as well as improve the data capabilities in the wider business.</div><h3 class="jobSectionHeader"><b><br>
Key Responsibilities</b></h3><div><br>
This is a broad and hands-on role with the chance to improve how Field uses data within and beyond the realms of GAIA&rsquo;s ecosystem</div><br>
<div></div><ul>
<li>
building and operating the production data pipelines and streaming integrations that ingest a wide range from market data to asset telemetry</li>
<li>partnering with our trading team to deliver the required data and capabilities for in-house forecasting model development</li>
<li>guiding and partnering with stakeholders in the wider business to build out integrations and analytical views over their data</li></ul><br>
<h3 class="jobSectionHeader"><b>
Skills, Knowledge and Expertise</b></h3><div><b><br>
The skills you&rsquo;ll need</b></div><ul>
<li>Comfortable writing production-grade Python and SQL</li>
<li>Hands-on data pipeline experience</li>
<li>Comfortable working in the cloud with infrastructure as code</li>
<li>Familiarity with modern data tooling across warehousing, transformation and business intelligence</li>
<li>Collaboration skills to work with a wide range of stakeholders e.g. engineers, business stakeholders and data scientists</li>
<li>Data product mindset</li>
<li><b>Nice-to-have</b>: Experience working with streaming or near-real-time pipelines</li>
<li><b>Nice-to-have</b>: Experience using LLMs to help non-technical users self-serve analytics</li></ul><br>
<h3 class="jobSectionHeader"><b>
Benefits</b></h3><div><b><br>
Package Details</b></div><div>
Salary: Salary: &pound;64,000 - &pound;78,000</div><div></div><div><br>
We&rsquo;re offering a competitive compensation package, including participation in our employee share scheme which rewards all employees for the growth of the business. You&rsquo;ll be awarded shares when you join, which will vest over four years - and as the business grows in size and value, so will your shares!</div><div></div><div><br>
We value our team&rsquo;s wellbeing and belonging so we invest approx &pound;5,000 a year on a range of perks, benefits and wellbeing activities, including regular team socials and events.</div><div></div><div><br>
Other benefits include</div><ul>
<li>Up to 10% Company wide bonus based on company performance</li>
<li>Hybrid working (blend of home and office working to suit individual needs)</li>
<li>&pound;2,000 per year to spend on your professional development</li>
<li>Private medical cover with Bupa from day one with the option to add family members.</li>
<li>Company Pension with 8% Contribution</li>
<li>Up to 12 days a year of Period Leave</li>
<li>Enhanced parental leave, for all new parents:<ul>
<li>6 months fully paid primary carer leave</li>
<li>3 months fully paid secondary carer leave</li>
<li>10 days fully paid leave for fertility treatment</li>
</ul></li><li>Fun co-working office space in Shoreditch, London</li>
<li>1 month work from anywhere, for those with a travel bug</li>
<li>1 day green leave to do something good for the environment</li>
<li>free lunch once a week - a great way to get to know people in the wider team</li>
<li>dog friendly office, feel free to bring your pooch along</li>
<li>Spill: our mental health benefit allowing every Fielder access to equal and unrestricted therapy and resources</li>
<li>Regular, optional team socials designed to be inclusive for everyone (not just the pub goers!)</li>
<li>Birthday carbon offset: a gift from Field to the world to celebrate your birthday</li>
</ul><div><b>A bit about Field</b></div><div></div><div><br>
Field is an international builder, owner, and operator of renewable infrastructure. Founded by a successful entrepreneur, we have robust BESS project pipelines across the UK, Italy, Spain, and Germany, backed by a recent &pound;200 million investment from DIF Capital Partners. Our mission is to grow internationally and develop a strong global BESS portfolio.</div><div></div><div><br>
We are an eclectic team with diverse backgrounds, from scaling billion-dollar tech startups to building energy companies and specializing in energy markets. You'll work with fun, curious, entrepreneurial people making a real impact. We're proving batteries are a viable energy solution now. Our ambitious plans include becoming Europe's leading clean energy player and expanding beyond batteries into new assets</div><div><br>
</div><div><b>Our Values</b></div><ul>
<li><b>Work for the team</b> - We are friendly and approachable. We make time for each other, value diverse perspectives, and learn and grow together.</li>
<li><b>Do it right</b> - We prioritise doing things right, never cutting corners. Safety comes first, and we consider our impact on communities and the environment. We act with integrity always.</li>
<li><b>Move fast</b> - We&rsquo;re doers. We take responsibility, deliver on promises, and get things done. FAST.</li>
<li><b>Know your stuff</b> - We&rsquo;re curious self-starters, always learning, adapting, and improving. No question is too small. We own our growth.</li></ul><div><br>
</div><div>
Read more about our values at www.field.energy</div><div></div><div><br>
Love the sound of Field but not sure this role is right for you? Have a look at our careers page and register your CV. We are always interested in candidates who have exposure to BESS and work within the Renewable Energy space. We&rsquo;d love to hear from you</div><div></div><div><b><br>
Equality, Diversity &amp; inclusion</b></div><div></div><div><br>
Diverse teams make better teams. Field is committed to creating a diverse and inclusive environment which is as representative as possible of our society. All qualified applicants will receive consideration for employment without regard to age, disability, gender expression, marriage/civil partnership status, pregnancy/maternity status, race, nationality, religion or belief, or sexual orientation. We published a blog discussing our findings and learnings from our first Equity, Diversity and Inclusion survey in March 2023 which you can read here.</div><div></div><div><br>
Still not convinced? See what our current team think about working here to find out why you should join us!</div><h3 class="jobSectionHeader"><b><br>
About FIELD</b></h3><div>
To reach Net Zero, we need to solve big challenges. Field will fund, build and run the renewable infrastructure we need to tackle these challenges. At Field, we will show that batteries are a totally viable part of our energy infrastructure - <b><i>now</i></b>, not in some distant future.</div><div></div><div><br>
And, we have ambitious plans to become the defining new clean energy player in Europe over the next few years, gradually expanding beyond batteries into new asset types.</div></div>

Software Engineer - Data

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