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data platform engineer

Goldman Sachs

<div><div><div><div><div><div><div><p><b>The Opportunity</b></p>
<p>
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.</p>
<p>
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.</p>
<p>
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.</p>
<p><b>
Role Summary</b></p>
<p>
As a <b>Data Engineer</b> in the <b>Lakehouse and AI Data Platform team,</b> 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.</p>
<p>
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.</p>
<p><b>
Key Responsibilities</b></p>
<p><b>
Pipeline Engineering</b></p>
<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.</li></ul>
<p><b>
Data Modelling and Curation</b></p>
<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.</li></ul>
<p><b>
Data Quality and Reconciliation</b></p>
<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.</li></ul>
<p><b>
Delivery and Partnership</b></p>
<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.</li></ul>
<p><b>
Skills and Experience</b></p>
<p><b>
Required</b></p>
<ul><li>
7-12+ years of experience</li><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 <b>Python</b> or <b>Java</b>.</li><li>
Good working knowledge of <b>SQL</b>, including troubleshooting, optimization 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.</li></ul><br>
<p></p>
<p><b>
Data Engineering Capability</b></p>
<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 normalized and denormalized 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 <b>Apache Spark</b>.</li><li>
Working knowledge of common data formats such as <b>JSON</b>, <b>Avro</b> and <b>Parquet</b>.</li><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.</li></ul><br>
<p></p>
<p><b>
Technology Environment</b></p>
<p>
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.</p>
<p><b>
Examples of technologies in scope include:</b></p>
<ul><li><b>
Data processing and logic:</b> ANSI SQL, Apache Spark, Kafka</li><li><b>
Data formats:</b> JSON, Avro, Parquet</li><li><b>
Platforms and storage:</b> Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ</li><li><b>
Engineering and deployment:</b> CI/CD tooling, containerized or Kubernetes-based deployment approaches where relevant</li></ul>
<p>
You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important.</p><br>
<p></p>
<p><b>
What We Are Looking For</b></p>
<p>
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.</p>
<p>
Stronger candidates will typically demonstrate:</p>
<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 interest in developing long-term expertise within the firm</li></ul></div></div></div></div></div></div><div><div><div><div><div><b>
We Offer Best-In-Class Benefits</b></div></div></div><p></p><div><div><div><div><div><div><div>
Healthcare &amp; Medical Insurance</div></div><p>
We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short-term disability, long-term disability, life, accidental death, labor accident and business travel accident insurance.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Holiday &amp; Vacation Policies</div></div><p>
We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Financial Wellness &amp; Retirement</div></div><p>
We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees&rsquo; priorities.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Health Services</div></div><p>
We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state-of-the-art on-site health centers in certain offices.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Fitness</div></div><p>
To encourage employees to live a healthy and active lifestyle, some of our offices feature on-site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre-approved amount).</p></div></div></div></div><p></p><div><div><div><div><div><div>
Child Care &amp; Family Care</div></div><p>
We offer on-site child care centers that provide full-time and emergency back-up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Benefits at Goldman Sachs</div></div><p>
Read more about the full suite of class-leading benefits our firm has to offer.</p></div></div></div></div></div></div></div></div><div></div>
<br><p>Opportunity Overview
CORPORATE TITLE
Vice President
OFFICE LOCATION(S)
New York
JOB FUNCTION
Software Engineering
DIVISION
Engineering Division
SALARY RANGE
USD 130,000 - 250,000</p>

Data Engineering - Data, Lakehouse and AI Data Platform Engineer - Vice President - New York

<div><div><div><div><div><div><div><p><b>The Opportunity</b></p>
<p>
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.</p>
<p>
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.</p>
<p>
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.</p>
<p><b>
Role Summary</b></p>
<p>
As a <b>Data Engineer</b> in the <b>Lakehouse and AI Data Platform team,</b> 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.</p>
<p>
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.</p>
<p><b>
Key Responsibilities</b></p>
<p><b>
Pipeline Engineering</b></p>
<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.</li></ul>
<p><b>
Data Modelling and Curation</b></p>
<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.</li></ul>
<p><b>
Data Quality and Reconciliation</b></p>
<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.</li></ul>
<p><b>
Delivery and Partnership</b></p>
<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.</li></ul><p><br>
</p><p></p><p><b>Skills and Experience</b></p>
<p><b>
Required</b></p>
<ul><li>
0-2+ years of experience</li><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 <b>Python</b> or <b>Java</b>.</li><li>
Good working knowledge of <b>SQL</b>, including troubleshooting, optimization 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.</li></ul><br>
<p></p>
<p><b>
Data Engineering Capability</b></p>
<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 normalized and denormalized 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 <b>Apache Spark</b>.</li><li>
Working knowledge of common data formats such as <b>JSON</b>, <b>Avro</b> and <b>Parquet</b>.</li></ul>
<p><b>
Technology Environment</b></p>
<p>
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.</p>
<p><b>
Examples of technologies in scope include:</b></p>
<ul><li><b>
Data processing and logic:</b> ANSI SQL, Apache Spark, Kafka</li><li><b>
Data formats:</b> JSON, Avro, Parquet</li><li><b>
Platforms and storage:</b> Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ</li><li><b>
Engineering and deployment:</b> CI/CD tooling, containerized or Kubernetes-based deployment approaches where relevant</li></ul>
<p>
You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important.</p><br>
<p></p>
<p><b>
What We Are Looking For</b></p>
<p>
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.</p>
<p>
Stronger candidates will typically demonstrate:</p>
<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 interest in developing long-term expertise within the firm</li></ul></div></div></div></div></div></div><div><div><div><div><div><b>
We Offer Best-In-Class Benefits</b></div></div></div><p></p><div><div><div><div><div><div><div>
Healthcare &amp; Medical Insurance</div></div><p>
We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short-term disability, long-term disability, life, accidental death, labor accident and business travel accident insurance.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Holiday &amp; Vacation Policies</div></div><p>
We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Financial Wellness &amp; Retirement</div></div><p>
We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees&rsquo; priorities.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Health Services</div></div><p>
We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state-of-the-art on-site health centers in certain offices.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Fitness</div></div><p>
To encourage employees to live a healthy and active lifestyle, some of our offices feature on-site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre-approved amount).</p></div></div></div></div><p></p><div><div><div><div><div><div>
Child Care &amp; Family Care</div></div><p>
We offer on-site child care centers that provide full-time and emergency back-up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available.</p></div></div></div></div><p></p><div><div><div><div><div><div>
Benefits at Goldman Sachs</div></div><p>
Read more about the full suite of class-leading benefits our firm has to offer.</p></div></div></div></div></div></div></div></div><div></div>
<br><p>Opportunity Overview
CORPORATE TITLE
Associate
OFFICE LOCATION(S)
New York
JOB FUNCTION
Software Engineering
DIVISION
Engineering Division
SALARY RANGE
USD 115,000 - 180,000</p>

Data Engineering - Data, Lakehouse and AI Data Platform Engineer - Analyst/Associate - New York

Nscale

<div>
 <strong>
  About Nscale
  <br/>
  <br/>
 </strong>
 Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve superior results by reducing the complexity of AI development. Our GPU cloud bolsters technical capabilities and directly supports strategic business outcomes, including cost management, rapid innovation, and environmental responsibility.
 <br/>
 <br/>
 We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you&rsquo;ll build trust through openness and transparency, where everyone is inspired to do their best work. If you join our team, you&rsquo;ll be contributing to building the technology that powers the future.
 <br/>
 <br/>
 <strong>
  About The Role (Job Purpose)
  <br/>
  <br/>
 </strong>
 We&rsquo;re looking for a
 <strong>
  Data Engineer
 </strong>
 to help design, build, and operate the data foundations that underpin Nscale&rsquo;s platform, internal operations, and customer-facing capabilities.
 <br/>
 <br/>
 This is a
 <strong>
  high-impact, early-stage role
 </strong>
 . You&rsquo;ll work closely with Operations, Infrastructure, Platform Engineering, Product, and Commercial teams to turn raw operational signals &mdash; from GPUs, clusters, customers, and internal systems &mdash; into reliable, scalable data products that ensure delivery at a previously unseen pace. You&rsquo;ll help define
 <em>
  how data is collected, modelled, served, and trusted
 </em>
 across the company, and have the opportunity to build on Palantir Foundry, as well as other products.
 <br/>
 <br/>
 This role is ideal for someone who enjoys building data systems from first principles, thrives in ambiguous environments, and wants to see their work directly influence product decisions, platform reliability, and customer outcomes.
 <br/>
 <br/>
 <strong>
  What You&rsquo;ll Be Doing (Responsibilities)
  <br/>
  <br/>
 </strong>
 <strong>
  Data Platform &amp; Architecture
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and build scalable, reliable data pipelines that ingest data from infrastructure, platform services, and business systems.
  </li>
  <li>
   Define data models and schemas that support operational workflows and use cases across the business, monitoring, and analytics.
  </li>
  <li>
   Clean, transform and structure the data to create a digital twin of Nscale.
  </li>
  <li>
   Implement permissioning and manage access and security of the Foundry implementation.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Data Products &amp; Enablement
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Create trusted datasets and metrics that power workflows and processes, internal tools, and customer-facing insights.
  </li>
  <li>
   Enable self-serve analytics by establishing clear data contracts, documentation, and semantic layers.
  </li>
  <li>
   Build use cases including but not limited to capacity planning, cost optimisation, reliability analysis, and customer reporting to drive our business forward.
  </li>
  <li>
   Collaborate with Product and Commercial teams to translate real-world questions into robust data solutions.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Reliability, Quality &amp; Governance
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Implement data quality checks, monitoring, and alerting to ensure data correctness and availability.
  </li>
  <li>
   Codify data lineage, freshness, and consistency across systems.
  </li>
  <li>
   Establish best practices around data versioning, access control, and governance appropriate for a fast-scaling company.
  </li>
  <li>
   Continuously improve system resilience and observability.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Early-Stage Ownership &amp; Growth
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Take end-to-end ownership of projects, from design through to production and iteration.
  </li>
  <li>
   Help define standards, tooling, and ways of working for data at Nscale.
  </li>
  <li>
   Contribute to technical decision-making as the company scales its platform and customer base.
  </li>
  <li>
   Act as a thought partner to engineers and operators, not just a service function.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About You (Skills / Qualifications)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Deep, hands-on experience building in Palantir Foundry, including ontology modelling, pipeline development, API integration, and large-scale data platform design.
  </li>
  <li>
   Strong proficiency in Python, with experience applying data engineering libraries and frameworks (e.g. Spark, PySpark, Dask, pandas) to work with large, complex datasets.
  </li>
  <li>
   Familiarity with API-driven data integration, including REST, GraphQL, and Foundry Action APIs.
  </li>
  <li>
   Practical experience working in Git-based development workflows, including code reviews, version control, and CI/CD pipelines.
  </li>
  <li>
   Comfort working in ambiguous, early-stage environments where requirements evolve quickly.
  </li>
  <li>
   Strong communication skills &mdash; able to explain data concepts clearly to technical and non-technical stakeholders.
  </li>
  <li>
   A bias toward ownership, pragmatism, and shipping useful solutions.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice to Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with cloud platforms (AWS, GCP, Azure) and infrastructure telemetry.
  </li>
  <li>
   Familiarity with distributed systems, monitoring data, or usage-based billing data.
  </li>
  <li>
   Experience supporting customer-facing data products or platforms.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Can Offer You
  <br/>
  <br/>
 </strong>
 At Nscale, you'll find a
 <strong>
  collaborative, supportive, and innovative environment
 </strong>
 where your contributions spark real impact. We're building something extraordinary, and we want you at the core.
 <br/>
 <br/>
 <ul>
  <li>
   Highly competitive package (base + equity) with reviews every 12 months. 🚀
  </li>
  <li>
   Join the fastest-growing tech startup, your chance to push boundaries, collaborate with brilliant minds, and make your mark on cutting-edge AI. ✨
  </li>
  <li>
   Expect a dynamic progression plan tailored to your ambitions. Grow by trying new things, leading, challenging the status quo, and owning your impact, always with our full support.
  </li>
  <li>
   Human-First Flexibility: We treat you as humans first. 🫶🏽 Our flexible workplace trusts Nscalers to deliver, giving you the autonomy to shape your day around life's moments.
  </li>
  <li>
   Join our thriving remote-first team. Geography is no barrier to impact or connection. We build seamless virtual collaboration, empowering you, wherever you work.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Interview Process
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Phone screen
  </li>
  <li>
   Coding interviews
  </li>
  <li>
   Hiring Manager interview
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Equal Opportunities Statement
  <br/>
  <br/>
 </strong>
 We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.
 <br/>
 <br/>
 If there&rsquo;s anything we can do to accommodate your specific situation, please let us know.
 <br/>
 <br/>
 The responsibilities outlined in this job description are not exhaustive and are intended to provide a general overview of the position. The employee may be required to perform additional duties, tasks, and responsibilities as assigned by management, consistent with the skills and qualifications required for the role.
 <br/>
 <br/>
 <em>
  For information on how Nscale handles candidate personal data, please see our Employee &amp; Candidate Privacy Notice: Here.
 </em>
</div>


Data Engineer

Cyera

<div><p><b>WHO WE ARE</b></p><p>
Come join the company reinventing data security, empowering businesses to realize the full potential of their data. As the leading data security platform purpose-built for the cloud era, Cyera&rsquo;s mission is to reinvent how businesses secure data, enable agile collaboration, and boldly pursue new business opportunities. Trusted by security teams at leading global businesses, our team is proving that data security is the next big thing in cyber. Backed by the world&rsquo;s leading investors and working with a large and growing list of Fortune 1000 companies, we are looking for world-class talent to join us as we usher in the new era of data security.</p><p></p><p><b><br>
THE OPPORTUNITY</b></p><p>
Cyera's analytics engineering team builds and operates an internal analytics and AI platform that serves as the company's central hub for data exploration, dashboards, and AI-powered insights. The platform supports go-to-market teams and powers customer-facing data products.</p><p>
As a Senior Full Stack Engineer, you'll co-own the platform alongside a small, high-impact team. This is a backend-heavy full-stack role: you'll spend most of your time in Python and AWS, with meaningful React/TypeScript work on the frontend. The platform integrates deeply with LLMs (Amazon Bedrock), Snowflake, and internal data pipelines, so you'll work at the intersection of software engineering, data infrastructure, and applied AI.</p><p>
This is not a typical internal tools role. The platform is actively replacing third-party BI tooling, has growing executive adoption, and is expanding in scope. You'll ship features that are used daily by leadership and cross-functional teams, with short feedback loops and high visibility.</p><p></p><p><b><br>
RESPONSIBILITIES:</b></p><ul><li>
Design, build, and maintain backend services powering the analytics platform (Python/FastAPI, DynamoDB, S3, AWS ECS).</li><li>
Develop and improve the React/TypeScript frontend, including the dashboard builder, data visualization, admin panels, and session management UI.</li><li>
Build and maintain LLM agent integrations, including tool orchestration, prompt management, and multi-agent workflows using Amazon Bedrock.</li><li>
Own platform reliability: session persistence, streaming stability, error handling, timeout management, and performance optimization.</li><li>
Design and implement role-based access control (RBAC), user provisioning (Okta), and data access policies.</li><li>
Build data visualization features, including chart rendering, SQL-driven widgets, interactive filters, and exportable reports.</li><li>
Collaborate with the analytics engineering team on Snowflake query patterns, dbt model integration, and data pipeline connectivity.</li><li>
Manage deployment infrastructure including ECS task definitions, CI/CD pipelines, and environment configuration.</li><li>
Participate in code reviews and help establish engineering standards as the platform team grows.</li></ul><br>
Requirements:<br>
<br>
<p><b>REQUIRED QUALIFICATIONS:</b></p><ul><li>
5+ years of professional software engineering experience, with at least 2 years building production web applications.</li><li>
Strong Python skills with production experience building APIs in FastAPI.</li><li>
Working proficiency in TypeScript and React (or equivalent modern frontend framework).</li><li>
Experience with AWS services, particularly ECS/Fargate, DynamoDB, and S3</li><li>
Solid understanding of REST API design, authentication/authorization patterns, and service architecture.</li><li>
Comfortable with SQL and working alongside data teams that use Snowflake and dbt.</li><li>
Experience with CI/CD, containerized deployments (Docker), and infrastructure debugging.</li><li>
Self-directed and comfortable owning features end-to-end in a small team with minimal hand-holding.</li></ul><p></p><p><b><br>
PREFERRED QUALIFICATIONS:</b></p><ul><li>
Experience integrating LLMs or AI models into production applications (prompt engineering, tool calling, streaming responses).</li><li>
Background in data visualization, charting libraries (D3, Recharts, Plotly), or BI platform development.</li><li>
Experience with DynamoDB data modeling, including GSI design and access pattern optimization.</li><li>
Familiarity with data warehousing concepts and analytics workflows.</li><li>
Prior experience in a high-growth SaaS or cybersecurity environment.</li><li>
Comfort working across the stack. You don't need to be a frontend specialist, but you're not afraid of CSS.</li></ul><p></p><p><b><br>
COMPENSATION INFORMATION:</b></p><p>
Compensation Range: $200,000-$220,000.</p><p>
The range represents total compensation, and may include incentive for sales roles, equity or benefits, as applicable.</p><p>
This compensation range represents Cyera&rsquo;s good faith and reasonable estimate of the range of possible compensation for this role at the time of posting, and Cyera may ultimately pay more or less than the posted range. The final salary for this position will be determined in Cyera&rsquo;s sole discretion, consistent with applicable law, and based on a variety of factors, including but not limited to the employee&rsquo;s work experience, skills, and qualifications for the role, as well as the needs of Cyera&rsquo;s business and other operational considerations.</p><p>
Final compensation will vary based on seniority and relevance of experience, location, and position requirements.</p><p>
This role may be eligible for potential merit increases based on factors such as individual or company performance, time in role, and other discretionary factors.</p><p></p><p><b><br>
BENEFITS - Why Cyera?</b></p><ul><li>
Ability to work remotely, with office setup reimbursement</li><li>
Competitive salary</li><li>
Unlimited PTO</li><li>
Paid holidays and sick time</li><li>
Health, vision, and dental insurance</li><li>
Life, short and long-term disability insurance</li></ul></div>

Senior Fullstack Engineer - US

NavitasPartners

<div><h3 class="jobSectionHeader"><b>Job Title:</b><b> Senior Data Engineer</b></h3>
<p><b>
Location:</b> New York, NY 10020</p>
<p></p>
<h3 class="jobSectionHeader"><b>Position Summary</b></h3>
<p>
We are seeking a highly experienced Senior Data Engineer to support the design, development, and optimization of large-scale data platforms within a financial services environment. This role focuses on building robust data pipelines, enabling advanced credit risk analytics, and ensuring compliance with regulatory standards.</p>
<p>
The ideal candidate will bring deep expertise in credit and counterparty risk, modern data engineering technologies, and cloud-based data platforms, while collaborating closely with cross-functional teams including risk, quant, and compliance stakeholders.</p>
<p></p>
<h3 class="jobSectionHeader"><b>Key Responsibilities</b></h3>
<h4 class="jobSectionHeader"><b>Data Architecture &amp; Engineering</b></h4>
<ul><li>Lead architecture and technical design discussions for credit risk data platforms</li>
<li>Design and implement scalable batch and streaming data pipelines using PySpark</li>
<li>Build ingestion frameworks for structured and unstructured data from upstream systems into cloud storage (e.g., S3/ADLS)</li>
<li>Implement data processing workflows using Medallion Architecture (Bronze, Silver, Gold layers)</li>
</ul><h4 class="jobSectionHeader"><b>Data Processing &amp; Optimization</b></h4>
<ul><li>Develop and optimize transformation logic for large-scale financial datasets</li>
<li>Ensure high data quality, auditability, and regulatory compliance</li>
<li>Apply optimization techniques such as partitioning, indexing, and schema evolution</li>
<li>Model and optimize risk metrics (e.g., PD, LGD, EAD, EPE, PFE, CVA) for analytics and reporting</li>
</ul><h4 class="jobSectionHeader"><b>Platform Integration &amp; Operations</b></h4>
<ul><li>Integrate with external risk engines and support orchestration of complex batch processes</li>
<li>Ensure platform reliability, observability, and data lineage tracking</li>
<li>Implement and maintain security standards (IAM, encryption, authentication protocols)</li>
<li>Troubleshoot production issues and provide ongoing support</li>
</ul><h4 class="jobSectionHeader"><b>Collaboration &amp; Documentation</b></h4>
<ul><li>Collaborate with data scientists, risk analysts, and business stakeholders</li>
<li>Contribute to API design and data contracts for internal and external consumers</li>
<li>Maintain comprehensive technical documentation for audit and compliance purposes</li>
<li>Participate in Agile development processes and ceremonies</li>
</ul><p></p><h3 class="jobSectionHeader"><b>Required Qualifications</b></h3>
<ul><li>12+ years of experience in data engineering or data development</li>
<li>Strong experience within financial services, particularly credit or counterparty risk</li>
<li>Expertise in regulatory frameworks such as Basel III/IV, IFRS 9, CECL, or FRTB</li>
<li>Advanced proficiency in Python and PySpark / Apache Spark</li>
<li>Hands-on experience with cloud platforms and data lake technologies (e.g., Databricks, Delta Lake)</li>
<li>Strong SQL skills including complex queries, joins, and performance optimization</li>
<li>Experience building data pipelines from multiple financial data sources</li>
<li>Familiarity with workflow orchestration tools (e.g., Airflow or similar)</li>
<li>Experience with CI/CD tools such as Git, Jenkins, or Azure DevOps</li>
<li>Cloud certification (e.g., AWS Certified Cloud Practitioner or equivalent)</li>
</ul><p></p><h3 class="jobSectionHeader"><b>Preferred Qualifications</b></h3>
<ul><li>Experience with large-scale financial risk systems and analytics platforms</li>
<li>Background in designing data architectures and maintaining data dictionaries</li>
<li>Experience working in Agile environments using tools such as JIRA or Confluence</li>
<li>Exposure to modern data governance and compliance practices</li>
</ul><p></p><h3 class="jobSectionHeader"><b>Skills &amp; Competencies</b></h3>
<ul><li>Strong analytical and problem-solving abilities</li>
<li>Excellent communication skills with both technical and non-technical stakeholders</li>
<li>Ability to work collaboratively with cross-functional teams</li>
<li>High attention to detail and commitment to data quality</li>
<li>Proactive, self-driven mindset with continuous learning approach</li>
</ul><p></p><h3 class="jobSectionHeader"><b>Work Environment</b></h3>
<ul><li>Fast-paced, data-driven financial services environment</li>
<li>High level of collaboration with global teams</li>
<li>Focus on regulatory compliance, data governance, and innovation</li>
</ul>
<p><i>For more details reach at</i><b><i> resumes@navitassols.com.</i></b></p></div>

Senior Data Engineer - SDE 26-04140

Equinox

<div><b>Company Description</b><p><b><br>
OUR STORY:</b></p><p>
Equinox Group is a high growth collective of the world's most influential, experiential, and differentiated lifestyle brands. We restlessly seek what is next for maximizing life - and boldly grow the lifestyle brands and experiences that define it. In addition to Equinox, our other brands, <b>SoulCycle and Equinox Hotels </b>are all recognized for inspiring and motivating members and employees to maximize life. Our portfolio of brands is recognized globally with locations within every major city across the United States in addition to London, Toronto, and Vancouver.</p><p><b>
OUR CODE:</b></p><p>
We are passionate about <b>high performance living</b> and we practice what we preach &ndash; investing time in our own health and fitness. We believe that everyone has untapped potential within them and it takes a <b>disruptive approach</b> to unleash it. We <b>dream big</b> and don&rsquo;t settle for the status quo. We <b>sweat the details</b>. We never accept less than <b>110%</b> to <b>help each other</b> deliver the Equinox experience and enable our members to get great results. We are obsessed with what&rsquo;s new, what&rsquo;s now, <b>what&rsquo;s next</b>. Never following, always leading, and living ahead of the moment in fashion, culture, and consumer behavior. We aren&rsquo;t just a company; we&rsquo;re a community vested in each other&rsquo;s success. We value <b>humility</b> and a <b>team approach</b> at every level of the company.</p><p>
If you are a high performing individual who is passionate about winning and inspiring others then we are excited to discuss career opportunities with you.</p><b><br>
Job Description</b><p><br>
Equinox is seeking a Data Engineer to join our technology team. This role is a hands-on position responsible for the build and continued evolution of the data platform, business applications and integration tools. We are looking for a hands on engineer that can recommend best practices to work with enterprise data. The ideal candidate is going to be a hands on engineer, and very strong with AWS Products to help build out data pipelines, create jobs, manage the quality of the data warehouse and integrated tools.</p><p>
This is a full-time role located in our NYC office.</p><p>
RESPONSIBILITIES</p><ul><li>
Design, develop, and maintain scalable, efficient data pipelines to support ETL/ELT processes across multiple sources and systems</li><li>
Partner with Data Science, Analytics, and Business teams to understand data needs, prioritize use cases, and deliver reliable datasets and models</li><li>
Monitor, optimize, and troubleshoot data jobs, ensuring high availability and performance of data infrastructure</li><li>
Build and manage data models and schemas in Redshift and other data technologies, enabling self-service analytics</li><li>
Implement data quality checks, validation rules, and alerting mechanisms to ensure trust in data</li><li>
Leverage AWS services like Glue, Lambda, S3, Athena, and EMR to build modular, reusable data solutions</li><li>
Drive improvements in data lineage, cataloging, and documentation to ensure transparency and reusability of data assets</li><li>
Create and maintain technical documentation and version-controlled workflows (e.g., Git, dbt)</li><li>
Contribute to and promote a culture of continuous improvement, mentoring peers and advocating for scalable and modern data practices</li><li>
Participate in sprint planning, code reviews, and team retrospectives as part of an Agile development process</li><li>
Stay current on industry trends and emerging technologies to identify opportunities for innovation and automation</li></ul><br>
<b>
Qualifications</b><br>
<ul><li>
6+ years of experience in software/data engineering, with a proven track record of building robust data systems (prior leadership or mentorship experience is a plus)</li><li>
Advanced Python, including experience building APIs, scripting ETL processes, and automating workflows</li><li>
Expert in SQL, with ability to write complex queries, optimize performance, and work across large datasets</li><li>
Hands-on experience with AWS data ecosystem including Redshift, S3, Glue, Athena, EMR, EC2, DynamoDB, Lambda, and Redis</li><li>
Strong understanding of data warehousing and data modeling principles (e.g., star/snowflake schema, dimensional modeling)</li><li>
Familiarity with dbt Labs and modern ELT/analytics engineering practices</li><li>
Experience working with structured, semi-structured, and unstructured data</li><li>
Knowledge of data governance, quality assurance, and observability tools to ensure data integrity and trust</li><li>
Proficiency in creating technical documentation, SOPs, and maintaining clear communication with cross-functional teams</li><li>
A problem-solving mindset, with the ability to take ownership and drive solutions from design to deployment</li></ul><p>
Pay Transparency: $145k - $160k</p><b><br>
Additional Information</b><p><b><br>
AS A MEMBER OF THE EQUINOX TEAM YOU WILL RECEIVE:</b></p><ul><li>
We offer competitive salary, benefits, and industry leading commission opportunities for club employees</li><li>
Complimentary Club membership</li><li>
Perks and incentives with our products and services including Personal Training, Pilates, Spa and Shop</li></ul><p>
This job description is intended to describe the general requirements for the position. It is not a complete statement of duties, responsibilities or requirements. Other duties not listed here may be assigned as necessary to ensure the proper operations of the department.</p><p><b>
Equinox is an equal opportunity employer. For more information regarding our career opportunities, please visit one of our clubs or our website at </b><b><i>https://careers.equinox.com/</i></b></p><p>
All your information will be kept confidential according to EEO guidelines. Must have a legal right to work in the United States.</p></div>

Sr. Data Engineer (ON-SITE)

Sunset

<div>
 <strong>
  About Sunset
  <br/>
  <br/>
 </strong>
 Sunset is building the data layer for real-world AI training. We work with frontier labs to turn messy, multi-modal enterprise data into the highest-quality training data on the market &mdash; sourced from the hundreds of venture-backed startups we've helped wind down.
 <br/>
 <br/>
 We're a fast-growing team based in-person in Dumbo, Brooklyn. Backed by Floodgate, Afore Capital, Hustle Fund, and incredible entrepreneurs.
 <br/>
 <br/>
 <strong>
  The Role
  <br/>
  <br/>
 </strong>
 As a Data Engineer at Sunset, you'll own the pipeline that turns raw, chaotic enterprise data into the highest-quality training data on the market. One of our core technical challenges is entity resolution and de-identification across different sources and modalities. An even deeper challenge is understanding the node structures and linkages well enough to effectively reconstruct the business world this data comes from. All of this happens on sensitive data, which means security and privacy aren't a separate workstream but are built into every pipeline, system, and decision we make.
 <br/>
 <br/>
 <strong>
  What You'll Work On
  <br/>
  <br/>
 </strong>
 You'll own problems end-to-end. Some examples of what you might tackle in your first 90 days:
 <br/>
 <br/>
 <ul>
  <li>
   Designing the de-identification layer that replaces PII with stable pseudonyms while preserving every relationship across every source
  </li>
  <li>
   Building coreference resolution across Slack threads, email chains, and Linear comments so that "me," "him," and first-name mentions all resolve to the right canonical entity
  </li>
  <li>
   Hardening how we ingest, store, and process sensitive client data &mdash; from encryption and access controls to audit trails and isolation boundaries
  </li>
  <li>
   Extending our entity resolution pipeline to handle new modalities &mdash; think audio, video, design files, or embedded references inside documents
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  You Might Be a Fit If
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You are a product minded engineer and have shipped data pipelines at scale
  </li>
  <li>
   You have strong Python and are comfortable across NER, record linkage, and coreference
  </li>
  <li>
   You take security and privacy seriously and have built systems where getting it wrong wasn't an option
  </li>
  <li>
   You want to own a hard, ambiguous problem end-to-end rather than wait for a PRD
  </li>
  <li>
   AI is deeply integrated into your workflow and life
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  This Role Might Not Be a Fit If
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You want to work remote or hybrid &mdash; we're in-person 5 days/week in Dumbo
  </li>
  <li>
   You want to do novel ML research &mdash; this role is applied, not research
  </li>
  <li>
   You prefer long planning cycles or narrow ownership
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Our Stack
  <br/>
  <br/>
 </strong>
 Python, Postgres, Redis, AWS. We pick tools based on the problem, not the other way around.
 <br/>
 <br/>
 <strong>
  Compensation &amp; Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   $180K&ndash;$280K base + meaningful equity
  </li>
  <li>
   100% covered medical, dental, and vision
  </li>
  <li>
   Unlimited PTO
  </li>
  <li>
   $500 in-office setup allowance
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  How We Hire
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Intro Chat (20 min) &ndash; mutual fit and interests
  </li>
  <li>
   Technical Session (1hr) &ndash; collaborative problem-solving
  </li>
  <li>
   Onsite (2&ndash;3 hrs) &ndash; product deep dive, system design, meet the team
  </li>
  <li>
   Quick references &rarr; Offer
   <br/>
   <br/>
  </li>
 </ul>
 Compensation Range: $180K - $280K
 <br/>
 <br/>
</div>


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858 data platform engineer jobs In New York

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Data Engineer

Senior Fullstack Engineer - US

Senior Data Engineer - SDE 26-04140

Sr. Data Engineer (ON-SITE)

Data Engineer