data analyst

data engineer

software engineer

data scientist

senior data engineer

data software engineer

CLAIR

<div><h2 class="jobSectionHeader"><b>About Clair</b></h2><p>
If you can send your friends money in seconds, why does it still take your employer two weeks to send your paycheck?</p><p>
At Clair, we are on a mission to create financial freedom for America's workers by giving them a digital banking platform that allows them to get paid as soon as they clock out of work. But we're not just another digital bank or on-demand pay provider. We meet Americans at their place of work by embedding our products within the scheduling, workforce management, and payroll apps they already use every day.</p><p>
Learn more about us at getclair.com/about</p><h3 class="jobSectionHeader"><b>
About the Role</b></h3><p>
As a Machine Learning Engineer on Clair&rsquo;s Data team, you will be responsible for transforming diverse financial data sources, including but not limited to Plaid transactions, into production-grade features, predictive signals, and modeling pipelines that power Clair&rsquo;s credit and underwriting systems.</p><p>
Your work will focus on building the core feature layer that our credit models depend on: extracting structure from messy financial data, designing robust predictive features, forecasting key user-level events (such as income timing or financial stability indicators), and ensuring that these features are efficiently deployed, monitored, and continuously improved.</p><p>
In addition to hands-on modeling and feature engineering, you will contribute to the development of Clair&rsquo;s Data Science platform &ndash; building tooling, automation, and infrastructure that make it easier to train, deploy, and monitor ML systems at scale.</p><p>
This role is ideal for someone who loves crafting meaningful features out of raw data, scaling ML systems in production, and driving the technical foundations of a modern financial ML stack.</p><h3 class="jobSectionHeader"><b>
Key Responsibilities</b></h3><ul><li><p>
Engineer high-quality features from financial and behavioral data to support credit modeling.</p></li><li><p>
Build and maintain scalable pipelines for feature computation, income detection, and financial signal extraction.</p></li><li><p>
Develop forecasting and predictive models for income timing, user stability, and financial behavior patterns.</p></li><li><p>
Deploy, monitor, and optimize ML models and feature pipelines in production using AWS, Snowflake, or other tooling.</p></li><li><p>
Contribute to the development of Clair&rsquo;s Data Science platform, including model deployment workflows, feature stores, and monitoring systems.</p></li><li><p>
Collaborate with engineering, product, and risk teams to understand their workflows and ensure data products have high availability for their use cases</p></li><li><p>
Prototype new modeling techniques and evaluate their impact on credit and underwriting performance.</p></li><li><p>
Communicate findings and technical decisions clearly to both technical and non-technical stakeholders.</p></li></ul><h3 class="jobSectionHeader"><b>
Qualifications</b></h3><ul><li><p>
5+ years of experience in machine learning engineering, data science, data engineering, or a related technical field.</p></li><li><p>
Strong experience in feature engineering, particularly with large-scale transactional or time-series datasets.</p></li><li><p>
Proficiency in Python, SQL, and modern ML frameworks (e.g., PyTorch, XGBoost, sci-kit learn).</p></li><li><p>
Experience building production ML pipelines and deploying models in cloud environments</p></li><li><p>
Strong understanding of data modeling, forecasting, and statistical analysis.</p></li><li><p>
Clear and effective communication skills when working with product, engineering, and business stakeholders.</p></li><li><p>
Demonstrated ability to execute end-to-end: from raw data exploration to production ML implementation.</p></li><li><p>
Software engineering proficiency with a sensible adherence to good software design patterns</p></li></ul><h3 class="jobSectionHeader"><b>
Things We Consider a Plus</b></h3><ul><li><p>
Experience with Plaid or similar financial data providers.</p></li><li><p>
Background in credit risk modeling, underwriting features, or financial signal extraction.</p></li><li><p>
Familiarity with MLOps tools (e.g., MLflow, SageMaker, Feature Stores, Airflow).</p></li><li><p>
Experience building or contributing to internal Data Science platforms.</p></li><li><p>
Knowledge of explainable ML techniques and regulated-model requirements.</p></li><li><p>
Prior work in fintech, credit, or payments.</p></li></ul><h3 class="jobSectionHeader"><b>
Additional Details</b></h3><p><b>
Location:</b> This is a hybrid position based out of <b>New York City</b>, you will be expected to come into the office at least three days a week (Tuesdays, Wednesdays, &amp; Thursdays) with additional days on occasion for client meetings. We&rsquo;re open to remote candidates whose experience and background strongly match the requirements of the role.</p><p><b>
Compensation: </b>The annual base salary for this role is $200,000 for NYC and SF-based candidates. The base pay for this role is determined using many factors, such as education, skills and experience and is reflective of Clair Series stage and size. Base pay is only one part of Clair&rsquo;s competitive total compensation package which includes equity, benefits and additional perks. The base pay range is subject to change and may be modified in the future.</p><p><i>
Clair will only contact candidates from @getclair.com email addresses. We will never ask for payments or sensitive personal information during the hiring process. If you happen to receive anything suspicious, please ignore it.</i></p><h2 class="jobSectionHeader"><b>
Need more convincing?</b></h2><p>
Apart from getting to work with our incredible team, here are some of the benefits you can expect when you join Clair:</p><ul><li><p>
Medical, Dental, &amp; Vision Coverage, with option to extend to your family</p></li><li><p>
Fully-paid parental leave</p></li><li><p>
Company-sponsored 401k, HSA, and FSA</p></li><li><p>
Unlimited vacation for salaried roles, generous PTO for hourly roles</p></li><li><p>
Work from home setup allowance</p></li><li><p>
Access to your earnings every day on Clair</p></li><li><p>
Company-sponsored short-term and long-term disability insurance</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
Equal Opportunity Employer Information</b></h2><p>
Clair is an equal opportunity employer and we value diversity at our company. We actively seek a diverse applicant pool and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.</p><p>
For questions, please email us at careers@getclair.com</p></div>

Machine Learning Engineer - Financial Data

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Are you passionate about Big Data, Distributed systems, and large scale datasets can be integrated with new state-of-the-art AI agent-friendly data interfaces? Be part of a team of world-class engineers and industry leading experts operating one of the largest big data platforms for advertising at Amazon scale.<br>
<br>
Key job responsibilities<br>
Join our team and take ownership of significant initiatives that solve some of the toughest technical challenges in big data:<br>
<ul><li>Design and build highly scalable, fault-tolerant data pipelines processing petabytes of advertising data</li><li>Architect new data paradigms that enable real-time analytics and machine learning applications</li><li>Collaborate with data scientists, product managers, and partner teams across Amazon Ads to deliver data solutions that drive business impact</li><li>Mentor junior engineers through code reviews, design discussions, and pair programming</li><li>Contribute to technical strategy and architectural decisions for our data platform</li><li>Build monitoring, alerting, and data quality frameworks to ensure reliability at scale</li></ul><br>
Our systems are built for stability and reliability, which means our on-call shifts are manageable and focused on continuous improvement rather than firefighting.<br>
<br>
About the team<br>
We're a collaborative team of engineers who are passionate about solving complex data challenges while maintaining a healthy work-life balance. Our engineers regularly work with latest technologies&mdash;recent projects include migrating our data lake to Apache Iceberg, implementing real-time streaming pipelines with Spark, and building unified and flexible reporting solutions. We invest heavily in your growth through mentorship programs, technical design reviews, and opportunities to present at internal tech talks. We believe in sustainable engineering practices with reasonable on-call rotations (typically one week per quarter) and flexible work arrangements.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>1+ years of big data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza experience</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>4+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>4+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience</li><li>Experience building and operating data pipelines using Apache Spark and Scala on Amazon EMR, spanning extraction, ingestion, batch and streaming processing. Data lake design with Apache Iceberg a plus.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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 visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, NY, New York - 158,100.00 - 213,800.00 USD annually</div><p></p>

Software Development Engineer - Big Data, Brand Metrics and Benchmarks

Intuit

<div><h2 class="jobSectionHeader"><b>Overview</b></h2><div>
Come join the Trust &amp; Safety Data Engineering Team in New York as a Staff Software Data Engineer. We are leveraging big data technologies to develop solutions to detect and combat fraudulent activities initiated by external users across all Intuit&rsquo;s products. Some of the technologies we are leveraging include Apache Spark, Athena, Redshift, Kafka, Hive, S3, EMR, AWS, and GCP. We foster an open team environment where we value direct interactions and working code above working in a cave.</div><p></p><div><br>
You will lead the entire product lifecycle for multiple big data solutions that are broad in scope and complexity, applying a full understanding of software engineering methodologies and industry best practices for data products. Work with Industry Experts; Senior, Staff and Principal Engineers, utilize specialized knowledge to develop, and maintain Intuit&rsquo;s data solutions.</div><p><b><br>
Responsibilities</b></p><p></p><div><br>
RESPONSIBILITIES</div><ul><li><div>
Own the tech vision and strategy for multiple domains or capabilities</div></li><li><div>
Drive Strategic Impact. Focus on the direct and strategic application of data to deliver measurable business outcomes, even if it means working with imperfect data to capture significant value.</div></li><li><div>
Hands-on development in all phases of the software life cycle.</div></li><li><div>
Build batch and real-time/streaming data pipelines that are able to handle large volumes of data</div></li><li><div>
Design data models</div></li><li><div>
Gather data needs from internal customers like product and analysts and translate</div></li></ul><div>
those requirements into a working big data solution design.</div><ul><li><div>
Partner with product managers, fraud analysts, data scientists, data architects, software engineers, and other data engineers from around the world.</div></li><li><div>
Participate in design and code reviews</div></li><li><div>
Designing/developing ETL jobs across multiple big data platforms and tools including S3, EMR, Hive, Spark SQL, PYSpark.</div></li><li><div>
Rapidly fix bugs and solve problems; effectively remediate defects</div></li><li><div>
Clean, transform and validate data for use in analytics and reporting</div></li><li><div>
Proactively monitor data quality and pipeline performance, troubleshoot and resolve data issues</div></li><li><div>
Collaborate effectively with senior engineers and architects to solve problems spanning their respective areas to deliver end-to-end quality in our technology and customer experience.</div></li><li><div>
Helps to align to overall strategies and reconcile competing priorities across the organization.</div></li><li><div>
Contribute to the design and architecture of projects across the data landscape.</div></li><li><div>
Actively stay abreast of industry best practices, share learnings, and experiment and apply cutting edge technologies while proactively identifying opportunities to enhance software applications with AI technology</div></li><li><div>
Participate in a scheduled on-call rotation to handle production incidents outside of business hours</div></li><li><div>
Mentor other team members and contribute to the growth of the team</div></li><li><div>
Be available to work in a hybrid mode (3 days in the office and 2 days remote per week)</div></li></ul><p><b><br>
Qualifications</b></p><div></div><ul><li><div><br>
8+ years of hand-on experience building big data solutions and ETL data pipelines using Apache Spark or similar technologies</div></li><li><div>
BS or MS in Computer Science, Data Engineering or related field</div></li><li><div>
Hands-on experience developing data solutions on the AWS platform (preferred), GCP, or Azure</div></li><li><div>
Experience with Agile Development, SCRUM, and/or Extreme Programming methodologies</div></li><li><div>
Expert in SQL, Python and Linux, and strong working knowledge of XML, JSON, YAML.</div></li><li><div>
Knowledgeable with tools and frameworks Docker, Spark, Jupiter Notebook, Databricks Notebook, Kubernetes, Feature Management Platforms, SageMaker</div></li><li><div>
Advanced experience with scripting language &ndash; Python or Shell is a must have</div></li><li><div>
Expert knowledge of software development methodologies and practices</div></li><li><div>
Experience with cloud platforms such as AWS, Azure or GCP - Amazon web services: EC2, S3, EMR, and Redshift or equivalent cloud computing approaches</div></li><li><div>
Strong expertise in Data Warehousing and analytic architecture</div></li><li><div>
Experience working with large data volumes, data visualization</div></li><li><div>
Experience with low-latency NoSQL datastores (such as DynamoDB, HBase, Redshift) is a plus</div></li><li><div>
Experience with building stream-processing applications using Spark Streaming, Flink, etc. is a plus</div></li><li><div>
Hands on experience in AI</div></li><li><div>
Solid communication skills</div></li><li><div>
Demonstrated expertise in Software design and architecture process.</div></li><li><div>
Experience with unit testing and data quality automation checks</div></li><li><div>
Should be results oriented, self-motivated, accountable and work under minimal supervision.</div></li></ul><p><br>
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:</p><p>
New York $ 197,000- $266,500</p></div><p></p>

Staff Data Engineer - Trust and Safety

Fanatics

<div><p><b>The Role</b></p>
<p>
As a Staff Software Engineer on the Streaming Data Platform team in Fanatics Ecosystem, you will design, build, and operate the backend services that sit at the core of our streaming infrastructure &mdash; the systems that ingest, process, and deliver data to consumers across the company.</p>
<p>
This is a hands-on technical leadership role. You'll write code, design systems, mentor engineers, and shape how the team builds and operates software. The right person has built streaming infrastructure before and knows what it takes to keep it running well at scale.</p>
<p><b>
Responsibilities</b></p>
<ul>
<li>Design and build backend services that power our streaming data infrastructure, including ingestion, processing, and delivery to downstream systems.</li>
<li>Drive large, multi-milestone projects from idea to production, ensuring they deliver outcomes that matter to the business.</li>
<li>Set technical direction for the team: architecture, code quality, patterns, and tooling.</li>
<li>Partner with leadership on roadmap and planning &mdash; you'll have a voice in what we build and why.</li>
<li>Collaborate with platform, data, and product teams to design service boundaries, APIs, and data contracts.</li>
<li>Own the test strategy for complex areas and push the team toward better testing habits and testable designs.</li>
<li>Build observability, reliability, and resilience into our systems and hold the team to that standard.</li>
<li>Coordinate across engineers and teams to deliver cross-cutting initiatives.</li>
<li>Help diagnose and resolve performance bottlenecks related to ingestion, throughput, and distributed system behavior.</li>
<li>Mentor engineers on craft, ownership, and collaboration.</li>
<li>Participate in on-call rotations, drive incident resolution, and make sure retros lead to lasting fixes.</li>
<li>Be open to occasional travel to Fanatics offices for meetings, events, or team gatherings.</li>
</ul>
<p><b>Technical Environment</b></p>
<ul>
<li>Long-lived backend services (Go)</li>
<li>Event-driven and streaming data systems (Kafka, Kafka Connect)</li>
<li>Stream processing frameworks (e.g., Kafka Streams, Flink)</li>
<li>Schema management and data contracts</li>
<li>Observability and monitoring for streaming systems</li>
<li>Infrastructure as code (Terraform)</li>
</ul>
<p><b>Qualifications</b></p>
<ul>
<li>7 +years of experience building and operating backend services at scale, with a track record of leading large technical initiatives.</li>
<li>Strong experience with Go.</li>
<li>Hands-on experience with Kafka or comparable streaming platforms. You've built and operated streaming infrastructure in production, including pipeline design, throughput tuning, and operational concerns like monitoring and incident response.</li>
<li>Familiarity with the broader streaming ecosystem &mdash; tools like Flink, Spark, or Iceberg, and patterns around partitioning, data skew, and event-driven architectures.</li>
<li>Ability to design whole systems and services with clear boundaries, well-defined APIs, and operational readiness from the start.</li>
<li>Experience driving multi-milestone projects that span teams and require cross-functional coordination.</li>
<li>Track record of influencing technical roadmaps and connecting engineering work to business strategy.</li>
<li>History of mentoring engineers and raising the level of engineering practice around you.</li>
<li>Solid understanding of distributed systems, service-oriented architectures, and system integrations at scale.</li>
<li>Clear communicator who can talk about technical work with both engineers and non-engineers.</li>
<li>Comfortable in a fast-moving environment where priorities shift and decisions happen quickly.</li>
<li>Experience with schema management, data contracts, or data governance patterns is a plus.</li>
<li>Experience building shared libraries, frameworks, or developer-facing tooling for streaming consumers is a plus.</li>
<li>Experience contributing to open-source data infrastructure or streaming projects is a plus.</li>
<li>Familiarity with infrastructure as code tools such as Terraform is a plus.</li>
</ul>
<p><i>If you possess some of these skills but not all of them, we still encourage you to apply!</i></p>
<p>
The salary range for this position is <b>$180,500 to $237,500</b>, which represents base pay only and does not include short-term or long-term incentive compensation. When determining base pay, as part of a final compensation package, we consider several factors such as location, experience, qualifications, and training. Remote employee may also be eligible for a home office setup stipend.</p><div>
Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting &amp; Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally.</div></div>

Staff Software Engineer - Streaming Data Platform

Horizon Media, Inc.

<div><div>Job Description</div><div><div><div>
About Horizon Commerce</div><div><div>
Horizon Commerce helps brands navigate and succeed in an increasingly complex retail media and ecommerce ecosystem. We combine advanced analytics, retail media intelligence, and proprietary technology to help clients measure incrementality, optimize investment decisions, and drive sustainable growth across major retail platforms. We value collaboration, ownership, and practical problem solving in a fast-paced, evolving environment.</div></div><div></div><div>
Job Description Summary</div></div><div><div>
The Data Solutions Engineer is responsible for designing, building, and maintaining scalable data pipelines and analytics models that support Horizon Commerce&rsquo;s retail media and commerce intelligence platforms. This role focuses on data engineering and analytics enablement, partnering closely with analytics, product, and client-facing teams to ensure high-quality, reliable data used for measurement, forecasting, and optimization.</div></div><div></div><div><div>
Key Responsibilities</div></div><div><ul><li>
Design, implement, and maintain scalable data pipelines supporting retail media and ecommerce analytics platforms</li><li>
Develop and optimize dbt models and SQL transformations to ensure accuracy, consistency, and performance across datasets</li><li>
Manage data ingestion from multiple external sources, including APIs, retail media platforms, and third-party data providers</li><li>
Monitor and troubleshoot workflow orchestration systems (e.g., Airflow), ensuring reliable and timely data delivery</li><li>
Partner with analytics and product teams to translate business requirements into efficient data models and metrics definitions</li><li>
Manage cloud-based data infrastructure (e.g., AWS services, Airflow, Snowflake), including permissions, environments, and usage optimization</li><li>
Implement and maintain version control, documentation, and CI/CD practices for data workflows to support transparency and reproducibility</li><li>
Proactively identify and automate manual or repetitive data processes to improve reliability and reduce operational overhead</li><li>
Collaborate with client-facing analysts and engineers to publish verified datasets and enable reporting, forecasting, and client deliverables</li><li>
Ensure data quality, integrity, and compliance through consistent validation, monitoring, and security best practices</li></ul></div><div></div><div><div>
Qualifications</div></div></div><div><div><ul><li>
5-8 years of experience in data engineering, analytics engineering, or data platform roles</li></ul></div><div><ul><li><div>
Experience identifying and automating manual data processes</div></li><li>
Exposure to infrastructure best practices such as CI/CD for data workflows</li><li>
Experience supporting data shares and client-facing data delivery workflows</li><li>
Experience maintaining or developing web scraping pipelines (e.g., Selenium)</li><li>
Experience working with retail media or ecommerce platform data (e.g., Amazon Ads, Walmart Connect, Target Roundel)</li><li>
Strong communication skills and the ability to explain technical concepts to cross-functional stakeholders</li><li>
Ability to operate independently and take ownership of critical production systems</li><li>
Experience using Git for version control and collaborative development workflows</li><li>
Experience managing service accounts, API credentials, and secure key-based authentication (e.g., public/private key management)</li><li>
Experience troubleshooting API integrations, authentication issues, schema changes, and pipeline failures</li><li>
Familiarity with AWS services supporting data platforms, including S3, Lambda, EC2, IAM roles, CloudWatch, and related infrastructure components</li><li>
Experience managing data ingestion processes such as Snowpipe or equivalent streaming/batch ingestion frameworks</li><li>
Advanced SQL skills and experience working with cloud data warehouses such as Snowflake, BigQuery, or Redshift</li><li>
Strong experience with dbt for data modeling, testing, and transformation best practices</li><li>
Experience working with ELT tools such as Fivetran and managing third-party data connectors</li><li>
Hands-on experience with workflow orchestration tools such as Airflow, including DAG management, scheduling, monitoring, and troubleshooting</li><li>
Strong proficiency in Python for building, maintaining, and troubleshooting production data pipelines</li></ul></div><div></div><div><div>
Preferred Qualifications</div></div><div><ul><li>
Bachelor&rsquo;s degree or equivalent experience in Computer Science, Data Science, Engineering, or a related quantitative field</li><li>
Experience working with retail media or ecommerce data</li></ul></div><div><ul><li>
Prior experience supporting client-facing analytics or consulting teams</li><li>
Experience with Git-based version control and collaborative development workflows</li><li>
Experience with analytics or business intelligence tools</li><li>
Familiarity with measurement concepts such as incrementality, attribution, and forecasting</li><li>
Familiarity with retail performance metrics such as ROAS, incremental revenue, and new-to-brand measurement</li></ul></div><div></div><div><div>
#LI-KG1</div><div>
#LI-HYBRID</div><div>
#HC</div></div></div><div></div><div><i>
Horizon Media is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.</i></div><div></div><div>
Salary Range</div>
$140,000.00 - $170,000.00<div></div><div><i>
A successful applicant&rsquo;s actual base salary may vary based on factors such as individual&rsquo;s skill sets, experience, training, education,</i><i> licensure/certifications,</i><i> and qualifications for the role. </i><i>As an organization, we take an aptitude and competency-based hiring approach.</i><i> </i><i>We provide a competitive total rewards package including a discretionary bonus and a variety of benefits including health insurance coverage, life and disability insurance, retirement savings plans, company paid holidays and unlimited paid time off (PTO), mental health and wellness resources, pet insurance, childcare resources, identity theft insurance, fertility assistance programs, and fitness reimbursement.</i></div></div>

Data Solutions Engineer

S&P Global

<b>About the Role:</b><br>
<b>Grade Level (for internal use): 12 The Team:</b><br>
You will be an expert contributor and part of the Rating Organization's Data Services Team. This team, who has a broad and expert knowledge on Ratings organization's critical data domains, technology stacks and architectural patterns, fosters knowledge sharing and collaboration that results in a unified strategy. All Data Services team members provide leadership, innovation, timely delivery, and the ability to articulate business value. Be a part of a unique opportunity to build and evolve S&P Ratings next gen analytics platform.
<br><br>
<b>Responsibilities and Impact:</b><br>
Design and develop efficient and scalable data pipelines between enterprise systems and analytics platform
<br><br>
Work closely with Data Science team and participate in development of feature engineering pipelines
<br><br>
Provide technical expertise in the areas of design and implementation of Ratings Integrated Data Facility with modern AWS cloud technologies such as S3, Redshift, EMR, and distributed computing frameworks
<br><br>
Build and maintain a data environment for speed, accuracy, consistency and 'up' time
<br><br>
Support analytics by building a world-class data lake environment that empowers analysts to determine insights into revenue and power products across the organization
<br><br>
Work with the machine learning engineering team to build a data eco system that supports AI products at scale
<br><br>
Ensure data governance principles adopted, data quality checks and data lineage implemented in each hop of the data
<br><br>
Partner with the chief data office, enterprise architecture organization to ensure best use of standards for the key data domains and use cases
<br><br>
Be in tune with emerging trends in Big data and cloud technologies and participate in evaluation of new technologies
<br><br>
Ensure compliance through the adoption of enterprise standards and promotion of best practice / guiding principles aligned with organization standards
<br><br>
<b>What We're Looking For: Basic Required Qualifications:</b><br>
BS or MS degree in Computer Science or Information Technology
<br><br>
8+ years of experience as data engineer at an innovative organization
<br><br>
4+ years of hands-on experience in implementing data lake systems using AWS cloud technologies such as S3, Redshift, EMR, and distributed computing frameworks (such as Spark, Hadoop, or Flink)
<br><br>
Expert managing AWS services (EC2, S3, Route 53, ELB, VPC, CloudWatch, Lambda) in a multi-account production environment
<br><br>
Experience with development frameworks and data integration technologies (such as Informatica, Talend, or Apache NiFi) and programming languages including Python, Scala, Java, or similar
<br><br>
Expert knowledge of Agile approaches to software development and able to put key Agile principles into practice to deliver solutions incrementally
<br><br>
<b>Additional Preferred Qualifications:</b><br>
Experience with machine learning libraries and frameworks (such as TensorFlow, PyTorch, Scikit-learn, or MLlib) is an added advantage
<br><br>
Exposure to R, SparklyR, and other R packages is a plus
<br><br>
Monitors industry trends and directions; develops and presents substantive technical recommendations to senior management
<br><br>
Financial services industry experience
<br><br>
Excellent analytical thinking, interpersonal, oral and written communication skills with strong ability to influence both IT and business partners
<br><br>
Ability to prioritize and manage work to critical project timelines in a fast-paced environment
<br><br>
<b>Compensation/Benefits Information (US Applicants Only):</b><br>
S&P Global states that the anticipated base salary range for this position is $149,302 – $202,267. Final base salary for this role will be based on the individual’s geographical location as well as experience and qualifications for the role.
<br>In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan.
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This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here .
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About S&P Global Ratings
<br>At S&P Global Ratings, our analyst-driven credit ratings, research, and sustainable finance opinions provide critical insights that are essential to translating complexity into clarity so market participants can uncover opportunities and make decisions with conviction. By bringing transparency to the market through high-quality independent opinions on creditworthiness, we enable growth across a wide variety of organizations, including businesses, governments, and institutions.
<br><b>S&P Global Ratings is a division of S&P Global (NYSE:</b> SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today.
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For more information, visit www.spglobal.com/ratings
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What’s In It For You?
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<b>Our Mission:</b><br>
Advancing Essential Intelligence.
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<b>Our People:</b><br>
We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.
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<b>Our Values:</b><br>
Integrity, Discovery, Partnership
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Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.
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<b>Benefits:</b><br>
We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global.
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<b>Our benefits include:</b><br>
<b>Health & Wellness:</b> Health care coverage designed for the mind and body.
<br><b>Flexible Downtime:</b> Generous time off helps keep you energized for your time on.
<br><b>Continuous Learning:</b> Access a wealth of resources to grow your career and learn valuable new skills.
<br><b>Invest in Your Future:</b> Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
<br><b>Family Friendly Perks:</b> It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
<br><b>Beyond the Basics:</b> From retail discounts to referral incentive awards—small perks can make a big difference.
<br><b>For more information on benefits by country visit:</b> https://spgbenefits.com/benefit-summaries
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<b>Global Hiring and Opportunity at S&P Global:</b><br>
At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.
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S&P Global has a Securities Disclosure and Trading Policy (“the Policy”) that seeks to mitigate conflicts of interest by monitoring and placing restrictions on personal securities holding and trading. The Policy is designed to promote compliance with global regulations. In some Divisions, pursuant to the Policy’s requirements, candidates at S&P Global may be asked to disclose securities holdings. Some roles may include a trading prohibition and remediation of positions when there is an effective or potential conflict of interest. Employment at S&P Global is contingent upon compliance with the Policy.
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<b>Recruitment Fraud Alert:</b><br>
If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here .
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Equal Opportunity Employer
<br>S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.
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If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.
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<b>US Candidates Only:</b> Know Your Rights: Workplace discrimination is illegal
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----------------------------------------------------------- 20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.2 - Middle Professional Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning)
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<b>Job ID:</b> 324302
<br><b>Posted On:</b> 2026-03-09
<br><b>Location:</b> New York, New York, United States

Big Data Engineer Lead

Team8

<div><p><b>About Dimer Health</b></p><p><b>
﻿</b>Dimer Health is a pioneering digital health company transforming transitional care. By combining advanced AI-driven technology with exceptional clinical delivery, we are redefining the patient journey and closing critical gaps in care from hospital to home.</p><p>
Our data science work focuses on understanding the drivers of patient outcomes and developing interventions that measurably improve care.</p><p><b>
Role Overview</b></p><p>
We are seeking a Data Scientist to help Dimer Health develop a deep understanding of patient outcomes and how to improve them. This role focuses on defining meaningful outcome metrics, building predictive models, and extracting actionable insights from structured and unstructured clinical data. The goal is not just to predict outcomes, but to understand their causes and work with clinicians to design and validate interventions that improve patient care.</p><p>
You will work closely with clinical leadership, product teams, and data infrastructure to turn complex healthcare data into measurable improvements in patient outcomes.</p><p><b>
Key Responsibilities</b></p>
Develop and refine meaningful patient outcome metrics to evaluate quality of care.<ul><li> Design analytical approaches to measure and track outcomes across patient populations</li><li>
Build machine learning models over structured and unstructured to predict patient outcomes and identify key risk factors</li><li>
Translate analytical findings into actionable insights that inform clinical and operational decisions</li><li>
Collaborate closely with clinicians to validate findings and develop strategies to improve outcomes</li><li>
Evaluate the impact of interventions and support evidence-based improvements to patient care</li><li>
Generate novel insights from clinical data and contribute to peer-reviewed publication.</li></ul><br>
Requirements:<br>
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<p><b>Requirements</b></p><ul><li>
3+ years of experience in data science, machine learning, or applied statistical analysis</li><li>
Experience building predictive models using real-world data</li><li>
Proficiency in Python for data analysis and machine learning</li><li>
Solid SQL skills and ability to independently explore and extract data from complex databases</li><li>
Experience applying modern NLP techniques, including LLM-based approaches, to extract insights from unstructured text data</li><li>
Sound statistical reasoning and experience designing analytical approaches for observational data</li><li>
Ability to work independently in ambiguous problem spaces</li>
Ability to collaborate effectively with clinicians and other domain experts<li> Experience working with healthcare or clinical data</li><li>
Preferred: Familiarity with EHR data, FHIR, or other healthcare data models</li></ul><p></p><p><b><br>
Location</b></p><ul><li>
Hybrid &ndash; Florham Park, NJ (preferred).</li><li>
Fully remote within the U.S. may be considered for exceptional candidates. <b>Compensation</b></li><li><b>
﻿</b>Annual Salary Range: $130K - $170K</li><li>
The displayed salary range reflects the minimum and maximum target for new hire salaries for the position across all locations. Within the range, individual pay is determined by factors including job-related skills, experience, relevant education or training. We typically make offers near the <b>midpoint </b>of the posted salary range. This role is equity-eligible as part of Dimer&rsquo;s long-term incentive program.</li></ul><p><b>
Benefits:
</b></p><p><b>﻿</b>Eligible</p><ul><li>
Flexible Paid Time Off</li><li>
Health Reimbursement Arrangement (HRA): We reimburse you for eligible medical, dental, or vision expenses, including the cost of your own individual health insurance plan purchased through your state&rsquo;s Health Insurance Marketplace (Exchange), up to a set amount each year.</li><li>
Basic Life Insurance - premium paid in full by Dimer Health .</li></ul><p><b>
</b>Please note that this position is not eligible for employer-sponsored visa programs. Candidates must reside in and be authorized to work in the United States. At this time, Dimer is only considering candidates who reside in and are authorized to work in the United States, excluding the following states: D.C., ND, OH, WA, WY. Dimer participates in the federal E-verify program, which confirms employment authorization of newly hired U.S. based employees. E-verify is not used as a tool to pre-screen candidates and is only initiated upon hire.</p><br>
Company:
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Team8 Health<br>
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Core Team:
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Yes</div>

Team8 Digital Health Start Up-Data Scientist

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