data scientist

data engineer

data analyst

senior data engineer

software engineer

data developer

FanDuel

<div>THE POSITION 
Our roster has an opening with your name on it

We are looking for a Data Engineer to join our growing data platform team and take end-to-end ownership of designing, building, and scaling the foundational data infrastructure that powers analytics, machine learning, and business decision-making across the company. In this role, you will independently drive the design and delivery of reliable, secure, and cost-efficient data platforms, enabling data engineers, analysts, and data scientists to do their best work.

You will lead technical efforts in close partnership with engineering, analytics, and security teams &mdash; improving platform reliability, performance, and developer experience for high-impact data workloads at scale. You will bring strong engineering judgment to ambiguous technical problems, drive architectural decisions, and actively contribute to growing the technical capability of the team.

The ideal candidate is an experienced engineer who takes ownership of complex systems end-to-end, solves ambiguous problems independently, and thrives in a fast-paced, collaborative environment.

If you're excited by building resilient data platforms and want to make a broad impact at a dynamic company, we'd love to hear from you.

In addition to the specific responsibilities outlined below, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs. 

THE GAME PLAN 
Everyone on our team has a part to play
<ul>
<li>Own the design, development, and delivery of scalable data pipelines and platform components built on Databricks and Airflow &mdash; from requirements through production &mdash; with clear accountability for reliability, performance, and maintainability.</li>
<li>Drive performance monitoring and optimization of data workflows: proactively identify bottlenecks, diagnose root causes, and implement improvements independently.</li>
<li>Lead design and code reviews, setting the bar for code quality, testability, and engineering standards across the team's data engineering work.</li>
<li>Make independent technical decisions on pipeline architecture, data modeling, and tooling trade-offs, grounded in scalability, cost efficiency, and operational simplicity.</li>
<li>Own operational excellence for production batch and near-real-time pipelines: build and maintain monitoring, alerting, and runbooks, and lead incident response and postmortems.</li>
<li>Build and maintain comprehensive documentation for pipelines, data models, and platform workflows that supports team knowledge-sharing and onboarding.</li>
<li>Partner with analytics, data science, and engineering teams to drive adoption of platform capabilities, enforce data governance standards, and deliver against shared roadmap commitments.</li>
<li>Mentor junior engineers through pairing, code review feedback, and technical guidance &mdash; actively contributing to the growth of engineering craft on the team.</li></ul> 


THE STATS 
What we're looking for in our next teammate

Minimum Qualifications
<ul>
<li>3+ years of experience with Apache Airflow or a comparable orchestration platform, including building and maintaining DAGs for production workloads, with strong command of retries, scheduling, dependencies, and sensor patterns.</li>
<li>3+ years of experience developing in Python, writing readable, testable, and maintainable code in a data engineering context.</li>
<li>3+ years of experience with Databricks or a comparable distributed data platform, including designing and delivering ETL/ELT pipelines using Delta Lake or similar technologies, and independently optimizing compute and query performance.</li>
<li>Demonstrated ability to design and own end-to-end data systems with a focus on scalability, reliability, and operational observability &mdash; not just pipeline execution, but the full delivery lifecycle.</li>
<li>Solid experience working in cloud environments (AWS, Azure, or GCP), including cloud storage, IAM, and managed services, with strong understanding of secure data access patterns.</li>
<li>Experience with infrastructure as code (Terraform preferred) and the ability to independently manage and evolve platform infrastructure deployments.</li>
<li>Proficiency with Git-based workflows and CI/CD practices as applied to data and platform engineering.</li>
<li>Strong engineering judgment when navigating ambiguous technical problems &mdash; able to independently scope, design, and deliver solutions without close supervision.</li>
</ul>
Preferred Qualifications
<ul>
<li>Experience mentoring junior engineers or leading technical initiatives within a data engineering team.</li>
<li>Familiarity with data quality, observability, or lineage tools (e.g., Monte Carlo, Datafold).</li>
<li>Experience with dbt and a clear understanding of how transformation layers fit into a modern data stack.</li>
<li>Exposure to data governance, privacy, or compliance practices.</li>
<li>Experience supporting BI, analytics, or data science teams in a platform or infrastructure capacity.</li> 
</ul>
ABOUT FANDUEL

FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including: America's #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry's unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.

In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company's affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

PLAYER BENEFITS 
We treat our team right

We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO &amp; sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here: FanDuel Total Rewards. *Benefits differ across location, role, and level.

FanDuel is an equal opportunities employer and we believe, as one of our principles states, &quot;We are One Team!&quot;. As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included. 

The applicable salary range for this position is $125,000 - $163,800 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits: medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.

FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email Benefits@fanduel.com.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. 


#LI-Hybrid</div>

Data Engineer

BlackRock

<div><div><div><div><div>Locations: New York, New York</div></div></div></div></div>
 <div><h2 class="jobSectionHeader">Job description</h2>
<div>About this role
Aladdin is BlackRock&rsquo;s unified technology and data platform used by BlackRock and many of the world&rsquo;s largest Asset Managers and Investors. The Aladdin Platform Engineering organization is the Engineering Pillar within Aladdin responsible for building and operating the technology platform that powers Aladdin and includes the Developer Platform, the Core Platform and the Control Platform. Within Aladdin Platform Engineering, we are looking to bring on a senior technology leader to be the Head of AI Developer Platform.
Responsibilities
1. Own AI Native SDLC &amp; Engineering Productivity<ul><li>
Define and operationalize an AIfirst, agent driven SDLC embedded into the Developer Platform, spanning design, build, test, release, and operate phases, including:<ul><li>
Agent assisted design, code generation, refactoring, and documentation</li><li>
Agent driven test generation, coverage analysis, defect intelligence, and built-in quality and resilience signals</li><li>
Intelligent release validation, change risk assessment, and deployment readiness</li><li>
Continuous functional, integration, regression, performance, and resilience testing orchestrated as first-class SDLC stages rather than post hoc controls</li><li>
Continuous learning loops that improve software, delivery workflows, and AI agents over time</li></ul></li><li>
AI Vendor, Tooling &amp; Platform Integration<ul><li>
Drive evaluation, selection, and governance of AI developer tools and vendors integrated into the AI Developer Platform, ensuring capabilities are secure, production grade, and aligned to Aladdin&rsquo;s architecture, risk posture, and engineering standards.</li><li>
Ensure AI tools are platform integrated rather than point solutions, delivered through standardized onboarding, quality gates, observability, lifecycle management, and Responsible AI controls in partnership with Risk, Security, Legal, and Architecture.</li></ul></li><li>
Lead adoption of PDLC agents delivered through the Developer Platform, aligned to core engineering personas and architecture/design principles:<ul><li>
Developers:</li><li>
Testers / QE:</li><li>
Operators / SREs:</li><li>
Ensure quality, resilience, and risk prevention are embedded as default behaviors within PDLC agents, rather than treated as separate processes or late-stage controls.</li></ul></li></ul>
2. Own the evolution of continuous validation capabilities across the SDLC, including:<ul><li>
Performance, load, spike, and concurrency testing integrated into CI/CD pipelines</li><li>
Chaos engineering and fault injection experiments executed in preproduction environments</li><li>
Game Day testing and operational readiness simulations to validate incident response, observability, and recovery paths</li><li>
Establish clear skill expectations and enablement paths for developers, testers, and operators working in an AI augmented delivery model,</li></ul>
3. AI Developer Platform Context Engineering &amp; Enablement<ul><li>
Own the workforce enablement and distribution layer for the Developer Platform (through IDEs), ensuring AI capabilities and PDLC agents are delivered as secure, reusable, composable platform services within Engineering Services rather than fragmented tools.</li><li>
Lead context engineering and context graph strategy for the Developer Platform, including:<ul><li>
Defining and evolving enterprise context graphs
</li><li>Ensuring AI agents and PDLC agents have governed access to the right context at the right time, with controlled blast radius</li></ul></li><li>
Driving reuse of context primitives across SDLC, agent-based validation, and operational workflows</li></ul>
4. Own platform level capabilities for test data and environment management, including:<ul><li>
Production aligned preproduction environments that enable reliable end-to-end validation</li><li>
Repeatable, governed test data strategies (refresh, reset/replay, synthetic data) that support functional, performance, and resilience testing</li><li>
Pre-Prod Environment stability, drift detection, and telemetry-based health signals as inputs to release decisions</li></ul><ul><li>
Be a Champion and Lead governance for context ownership, freshness, versioning, and reuse to prevent drift and repeated failures at scale.</li></ul>
5. Engineering Excellence, Culture &amp; Leadership<ul><li>
Build and lead a high-performance, globally distributed AI Developer Platform organization within Engineering Services.</li><li>
Evangelize AI native, agent driven delivery practices across Aladdin while balancing innovation, operational stability, and risk discipline.</li></ul>
7. Governance, Risk &amp; Responsible AI<ul><li>
Own policy, governance, and control frameworks for AI usage and PDLC agents within the Developer Platform, ensuring alignment with firmwide risk, compliance, and Responsible AI standards.</li><li>
Own and mitigate technology and AI related risks for the Developer Platform, representing Engineering Services in risk and control governance forums.</li></ul>
8. Collaboration &amp; Enterprise Impact<ul><li>
Work closely with business leaders, product managers, domain architects, and delivery teams to translate business requirements into scalable, secure AI Developer Platform and PDLC agent capabilities.</li><li>
Collaborate with Platform Engineering, Product Engineering, Product leadership to ensure the Developer Platform meets the growth demands of Aladdin&rsquo;s clients and partners.</li></ul>
For New York, NY Only the salary range for this position is USD$275,000.00 - USD$350,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.

Our benefits 
 
To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work model
BlackRock&rsquo;s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person &ndash; aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.
About BlackRock
At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children&rsquo;s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.
This mission would not be possible without our smartest investment &ndash; the one we make in our employees. It&rsquo;s why we&rsquo;re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.<div>
For additional information on BlackRock, please visit @blackrock<div>
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 | Twitter: @blackrock<div>
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 | LinkedIn: www.linkedin.com/company/blackrock<div>
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BlackRock is proud to be an equal opportunity workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC&rsquo;s Know Your Rights poster and its supplement<div>
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 and the pay transparency statement<div>
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.</div><div>
BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email Disability.Assistance@blackrock.com<div>
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. All requests are treated in line with our privacy policy<div>
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.<div>
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BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.</div>
<div><div>Job Requisition #
 
R261411</div></div></div>

Head of AI Developer Platform

Shields Group Search

<div>
 
 
 Data Engineer
 
 
 
 
 Hybrid in NYC
 
 
 
 
 Full-Time
 
 
 
 
 $175,000-$225,000 base + upside depending on experience
 
 
 
 
 
 
 
 About the Company
 
 
 
 Shields Group Search is partnering with an innovative private banking and wealth infrastructure company building modern tools for modern clients. Their platform is designed to help private investors access liquidity more easily while driving transparency into historically opaque markets, including fine art and commercial real estate.
 
 
 
 
 
 They are hiring a
 
 Data Engineer
 
 to help build a world-class data infrastructure that supports the modernization of private banking for independent wealth managers and family offices. This person will be responsible for designing, building, and maintaining robust data pipelines, ETL processes, and data warehousing solutions that enable analytics and drive insights across the platform.
 
 
 
 
 
 You will work closely with engineering and product teams to architect scalable, reliable data systems. The stack includes
 
 Python, SQL, cloud data warehousing platforms, and modern data engineering tooling
 
 .
 
 
 
 
 
 
 About the Role
 
 
 
 This position reports directly to the
 
 Head of Engineering
 
 . The ideal candidate will have meaningful educational and/or professional experience designing and implementing scalable data systems, building ETL pipelines, and writing clean, maintainable, well-tested code.
 
 
 
 
 
 This team is looking for someone who is genuinely excited to spend most of their day coding and building scalable systems, while also contributing architectural input. They would strongly prefer someone in
 
 NYC
 
 , and
 
 2-3 days per week in-office
 
 should be expected. They also want someone who is comfortable building with and using
 
 agentic systems
 
 . This is not the right fit for someone optimizing primarily for work/life balance.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Participate in the full software development life cycle from planning to deployment
 </li>
 <li>
 Design and build scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources
 </li>
 <li>
 Collaborate with the team to design, develop, unit test, and support new features
 </li>
 <li>
 Strive for high quality and rapid output through agile software development best practices
 </li>
 <li>
 Architect data warehouses and data lakes, optimizing for query performance and cost efficiency
 </li>
 <li>
 Perform code reviews and provide constructive feedback to peers
 </li>
 <li>
 Maintain and improve the tech stack
 </li>
 <li>
 Develop flexible and well-structured data pipelines and data warehouse schemas
 </li>
 <li>
 Implement effective security protocols, data protection measures, and storage solutions
 </li>
 <li>
 Troubleshoot, debug, and upgrade software
 </li>
 <li>
 Ensure software meets all requirements of quality, security, and configurability
 </li>
 <li>
 Contribute to documentation, tests, and automation pipelines
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Software Engineering, or a related field
 </li>
 <li>
 Minimum of 3 years of experience in data engineering, ETL development, or analytics engineering, ideally within fintech or financial services
 </li>
 <li>
 Advanced proficiency in Python and SQL for data pipeline development and analysis
 </li>
 <li>
 Familiarity with CI/CD tools
 </li>
 <li>
 Experience with data warehousing platforms such as Snowflake, BigQuery, Redshift, or similar, as well as modern ETL tools
 </li>
 <li>
 Strong knowledge of the software development lifecycle
 </li>
 <li>
 Experience with testing and debugging
 </li>
 <li>
 Proficient understanding of code versioning tools such as Git
 </li>
 <li>
 Excellent problem-solving skills and attention to detail
 </li>
 <li>
 Excellent communication and teamwork skills
 </li>
 <li>
 Ability to work independently and take initiative
 </li>
 <li>
 Willingness and ability to build with agentic systems in a practical, hands-on way
 </li>
 </ul>
 
 
 
 
 
 Why This Role
 
 
 
 This is an opportunity to help architect a state-of-the-art platform and partner with an experienced leadership team during a period of rapid development. The team has additional flexibility on compensation for stronger candidates, with total base salary landing closer to
 
 $200,000-$225,000
 
 for candidates with more experience.
 
</div>

G-III Apparel Group

<div>
 
 
 Data Engineer
 
 
 
 G-III Apparel Group
 
 
 
 
 
 
 Department:
 
 Data &amp; Analytics
 
 
 
 Reporting To:
 
 VP Data Insights
 
 
 
 Location (On-Site):
 
 New York, NY - Fashion District
 
 
 
 
 
 
 About G-III Apparel Group, Ltd. | www.g-iii.com
 
 
 
 G-III Apparel Group is a global leader in design, sourcing, manufacturing, distribution, and marketing. We bring excitement and confidence to customers through the fashion we create. With more than 30 owned and licensed brands, including some of the most recognized names in global fashion, our success is driven by entrepreneurial thinking, operational excellence, and strong industry partnerships.
 
 
 
 
 
 
 Position Summary
 
 
 
 The Data Engineer is responsible for building and maintaining the data infrastructure that supports analytics, reporting, and operational decision-making across the organization. Reporting to the VP of Data Insights, this role develops scalable data pipelines and reliable datasets used by internal teams, business partners, and analytics platforms. The Data Engineer will work closely with data scientists, engineers, and business stakeholders to ensure high-quality, accessible data that supports the company&rsquo;s broader data and analytics strategy.
 
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Design, build and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data across enterprise systems
 </li>
 <li>
 Prepare, cleanse, and structure large datasets to support analytical modeling, reporting, and operational decision-making
 </li>
 <li>
 Implement data quality frameworks, validation rules, and monitoring systems to ensure data integrity and accuracy
 </li>
 <li>
 Partner with data scientists and analytics teams to support feature engineering and data preparation for quantitative analysis
 </li>
 <li>
 Work with engineering teams to implement automated anomaly detection and data monitoring solutions
 </li>
 <li>
 Serve as a subject-matter expert on internal datasets, including definitions, lineage, and quality standards
 </li>
 <li>
 Collaborate with product owners, business stakeholders, and systems teams to deliver reliable data products and services
 </li>
 <li>
 Design and maintain data models, data warehouses, and modern data architectures such as data lakes and data marts
 </li>
 <li>
 Contribute to the development of data governance standards, data documentation, and metadata management practices
 </li>
 <li>
 Support continuous improvement of the data platform through automation, testing, and performance optimization
 </li>
 <li>
 Ensure timely and reliable data delivery to support operational and strategic business needs
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 
 Required:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or equivalent practical experience
 </li>
 <li>
 3+ years of experience in data engineering or a similar data infrastructure role
 </li>
 <li>
 Strong proficiency in SQL and experience working with large relational datasets
 </li>
 <li>
 Programming experience in Python (including data processing libraries such as PySpark)
 </li>
 <li>
 Experience designing and implementing ETL/ELT pipelines and data integration workflows
 </li>
 <li>
 Experience with modern cloud platforms such as AWS, Azure, or GCP
 </li>
 <li>
 Working knowledge of data warehousing concepts, including data lakes, operational data stores, and dimensional modeling
 </li>
 <li>
 Familiarity with modern data orchestration and transformation tools (e.g., Airflow, Databricks, Data Factory, or similar)
 </li>
 <li>
 Understanding of data modeling, data governance, and data quality best practices
 </li>
 <li>
 Experience working in collaborative engineering environments using Git, CI/CD pipelines, and automated testing frameworks
 </li>
 <li>
 Strong analytical and problem-solving skills with the ability to communicate technical concepts clearly to both technical and non-technical audiences
 </li>
 <li>
 Ability to manage multiple priorities and deliver high-quality work in a fast-paced environment
 </li>
 </ul>
 
 
 
 
 
 Preferred:
 
 
 <ul>
 <li>
 Experience building scalable pipelines using Spark or distributed processing frameworks
 </li>
 <li>
 Familiarity with Azure data services such as Azure Data Factory, Microsoft Fabric, Synapse or Databricks
 </li>
 <li>
 Exposure to streaming or real-time data architectures
 </li>
 <li>
 Experience implementing data quality frameworks and governance programs
 </li>
 <li>
 Familiarity with business intelligence tools such as Power BI
 </li>
 <li>
 Prior experience in retail, fashion, or consumer products industries
 </li>
 <li>
 Experience leveraging AI-assisted development tools (e.g., Copilot, GPT-based coding assistants) to improve engineering productivity
 </li>
 <li>
 Master&rsquo;s degree in a related quantitative or technical field
 </li>
 </ul>
 
 
 
 
 
 What We Offer
 
 
 <ul>
 <li>
 Competitive base salary and performance-based incentives
 </li>
 <li>
 Comprehensive medical, dental, and vision benefits
 </li>
 <li>
 401(k) with company match
 </li>
 <li>
 Paid time off, holidays, and company-sponsored wellness benefits
 </li>
 <li>
 Employee discounts across G-III brands
 </li>
 <li>
 A collaborative, entrepreneurial work environment with career growth opportunities
 </li>
 </ul>
 
 
 
 
 
 Compensation
 
 
 
 
 Salary Range: $120,000 &ndash; $135,000 base (commensurate with experience)
 
 
 
 
 Please note that the foregoing compensation information is a good-faith assessment associated with this position only and is provided pursuant to the New York City Salary Transparency Law.
 
 
 
 
 
 
 
 G-III&rsquo;s owned brands include DKNY, Karl Lagerfeld Paris, Donna Karan, Vilebrequin, Sonia Rykiel, G.H. Bass, Bass Outdoor, Andrew Marc, Eliza J., G-III Sports and more. G-III holds licenses for Calvin Klein, Tommy Hilfiger, Cole Haan, Dockers, Guess?, Kenneth Cole, Levi&rsquo;s, Vince Camuto, Margaritaville, and others. The company also operates retail stores for DKNY, Karl Lagerfeld Paris, and Donna Karan.
 
 
</div>

Stuut Technologies

<div>
 Stuut is transforming accounts receivable for B2B companies&mdash;making collections smarter and faster for companies that have historically relied on manual processes that are labor intensive and costly. Our platform is gaining traction with finance teams across industrials, chemicals, and manufacturing sectors from Fortune 10 brands to scaling midmarkets. We're backed by top-tier investors including a16z, Khosla, Activant, 1984 Ventures and Page One.
 
 
 
 The Role
 
 
 
 We are hiring a Data Engineer to build the data foundation that powers Stuut's intelligence layer. You'll work closely with our product and engineering teams to transform raw financial data into actionable insights that help our customers get paid faster. This is a foundational role, you'll be our first data hire, which means you'll shape everything from our data architecture to how we think about analytics.
 
 
 This is a high-impact role for someone who can think strategically about data infrastructure while rolling up their sleeves to build pipelines, models, and systems from scratch. You'll translate messy data into clean, reliable datasets that drive product decisions, customer insights, and business growth. If you've ever wanted to own the entire data stack at a fast-growing company, this is it.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build and own our data infrastructure from the ground up, design pipelines that ingest, transform, and model data from customer ERPs, payment processors, and internal systems
 </li>
 <li>
 Partner with product and engineering to embed data quality and observability into everything we ship
 </li>
 <li>
 Create the analytics foundation that helps our customers understand payment patterns, collection trends, and cash flow predictions
 </li>
 <li>
 Implement DataOps best practices to ensure our data is timely, accurate, and trusted across the organization
 </li>
 <li>
 Collaborate with leadership to define KPIs, build dashboards, and surface insights that drive strategic decisions
 </li>
 <li>
 Scale our data platform as we grow from dozens to hundreds of customers, anticipating needs before they become bottlenecks
 
 
 </li>
 </ul>
 
 You Might Be a Fit If You&hellip;
 
 
 
 <ul>
 <li>
 Have 3+ years of hands-on experience building production data pipelines using Python
 </li>
 <li>
 Know your way around SQL and modern data warehouses; bonus if you've worked with Snowflake, BigQuery, or Redshift
 </li>
 <li>
 Have experience implementing ETL/ELT workflows at scale using tools like Airflow, dbt, or similar
 </li>
 <li>
 Understand data modeling fundamentals and can design schemas that balance performance with flexibility
 </li>
 <li>
 Have worked with messy, real-world data from SaaS APIs, databases, or third-party integrations
 </li>
 <li>
 Thrive in ambiguity and get energized by building something new rather than inheriting someone else's stack
 </li>
 <li>
 Care deeply about data quality and believe that great analytics start with great infrastructure
 </li>
 <li>
 Have experience (or strong interest) in fintech, B2B SaaS, or financial data, understanding AR/AP workflows is a big plus
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 <ul>
 <li>
 Top-of-market salary and equity package
 </li>
 <li>
 Benefits (for U.S.-based full-time employees)
 </li>
 <li>
 Medical, dental &amp; vision insurance coverage for you
 </li>
 <li>
 401(k) &amp; Match
 </li>
 <li>
 Equity
 </li>
 <li>
 Flexible PTO
 </li>
 <li>
 Parental Leave
 
 
 </li>
 </ul>
 Compensation Range: $135K - $190K
 
 
</div>

Praxis

Java eTrading Developer (Fixed Income) &ndash; NYC (W9)We are looking for a Java eTrading Developer based in New York City with experience in Fixed Income Capital Markets. This is a W9 contractor position.Location: New York City Work Type: Hybrid (2-3 day per week) Employment Type: W9 ContractorResponsibilities<ul><li>Develop and maintain Java-based eTrading applications</li><li>Work with Fixed Income trading systems and market data</li><li>Build REST APIs and microservices</li><li>Support pricing, quotes, and order management workflows</li><li>Collaborate with trading and business teams</li></ul>Requirements<ul><li>Strong Java experience (Java 6+)</li><li>Spring / Spring Boot</li><li>REST API development</li><li>Experience with electronic trading (eTrading) systems</li><li>Knowledge of Fixed Income products (Bonds, Treasuries, Yield/Pricing)</li><li>Understanding of trading lifecycle (Front Office preferred)</li><li>Experience with messaging systems (Kafka, MQ, JMS)</li><li>Market data experience</li><li>SQL and Linux/Unix environment</li><li>Microservices architecture</li></ul>Nice to Have<ul><li>FIX Protocol</li><li>Investment banking experience</li><li>Trading platforms</li><li>AWS or cloud experience</li></ul>Pay: $15,000.00 - $18,000.00 per monthWork Location: Hybrid remote in New York, NY 10010

Java eTrading Developer (Fixed Income) — NYC

Sunset

<div>
 
 About Sunset
 
 
 
 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.
 
 
 We're a fast-growing team based in-person in Dumbo, Brooklyn. Backed by Floodgate, Afore Capital, Hustle Fund, and incredible entrepreneurs.
 
 
 
 The Role
 
 
 
 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.
 
 
 
 What You'll Work On
 
 
 
 You'll own problems end-to-end. Some examples of what you might tackle in your first 90 days:
 
 
 <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
 
 
 </li>
 </ul>
 
 You Might Be a Fit If
 
 
 
 <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
 
 
 </li>
 </ul>
 
 This Role Might Not Be a Fit If
 
 
 
 <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
 
 
 </li>
 </ul>
 
 Our Stack
 
 
 
 Python, Postgres, Redis, AWS. We pick tools based on the problem, not the other way around.
 
 
 
 Compensation &amp; Benefits
 
 
 
 <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
 
 
 </li>
 </ul>
 
 How We Hire
 
 
 
 <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>
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 Quick references &rarr; Offer
 
 
 </li>
 </ul>
 Compensation Range: $180K - $280K
 
 
</div>

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