Goldman Sachs on cord

Goldman Sachs

Software Engineer

External position
London, UK
Hiring internally for Goldman Sachs?
Finance
We believe progress is everyone’s business.
Posted
2 weeks ago
Checked
cord regularly checks that external positions are still open
16 hours ago

Skills & Experience

Job roles: Data Engineer
Experience level: Entry, Junior, Mid
Core skills considered: Python, Java, SQL, JSON
Other skills considered: Data Pipelines, Data Modeling, CI/CD

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: On-site
Visa sponsorship: Not available

Job Description

As a Data Engineer in the Lakehouse and AI Data Platform team, you will design, build, test and support data pipelines and curated datasets on the firm'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.

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.


Key Responsibilities

Pipeline Engineering

  • Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform.
  • Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability.
  • Where needed, build reusable tooling to improve delivery, consistency and operational support.
  • Ensure data pipelines are production-ready, well tested and operationally supportable.

Data Modelling and Curation

  • Develop raw, refined and curated datasets that support analytics, reporting and AI use cases.
  • Apply sound data modelling principles to represent business entities, relationships and historical change accurately.
  • Work with consumers to shape data products that are usable, well documented and aligned to business needs.

Data Quality and Reconciliation

  • Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets.
  • Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise.
  • Contribute to clear standards for testing, monitoring and issue resolution.
  • Contribute to practical improvements in testing, monitoring or reconciliation tooling where these strengthen platform reliability and day-to-day delivery.

Delivery and Partnership

  • Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations.
  • Communicate clearly on progress, risks, dependencies and design choices, including where delivery would benefit from improvements to shared platform tooling.
  • For more senior candidates, take a broader role in technical leadership, task breakdown and support for junior engineers.

Skills and Experience

Required

  • Bachelor's or master's degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise.
  • Strong hands-on programming experience in Python or Java.
  • Good working knowledge of SQL, including troubleshooting, optimisation and data analysis.
  • Ability to learn new tools, internal platforms and delivery workflows quickly.
  • Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices.

Data Engineering Capability

  • Understanding of temporal data modelling, including the handling of historical state and change over time.
  • Knowledge of schema design, schema evolution and data compatibility considerations.
  • Understanding of partitioning, clustering and other techniques used to improve data performance at scale.
  • Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys.
  • Practical approach to data quality, reconciliation and root-cause analysis.
  • Experience building or supporting production data pipelines in a collaborative engineering environment.
  • Experience working with distributed data processing frameworks such as Apache Spark.
  • Working knowledge of common data formats such as JSON, Avro and Parquet.

For More Experienced Candidates

  • Stronger ownership of technical design across multiple datasets or pipeline domains.
  • Experience guiding implementation standards, code quality and engineering practices within a team.
  • Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers.

Technology Environment

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.

Examples of technologies in scope include:

  • Data processing and logic: ANSI SQL, Apache Spark, Kafka
  • Data formats: JSON, Avro, Parquet
  • Platforms and storage: Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ
  • Engineering and deployment: CI/CD tooling, containerised or Kubernetes-based deployment approaches where relevant

You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important.


What We Are Looking For

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.

Stronger candidates will typically demonstrate:

  • sound judgement in technical trade-offs
  • attention to detail in data correctness and testing
  • a clear and structured approach to problem solving
  • willingness to work closely with stakeholders and partner teams
  • an ability to identify when delivery problems would be better solved through reusable tooling or platform improvements
  • an interest in developing long-term expertise within the firm
Software Engineer at Goldman Sachs
Position posted 2 weeks ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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