data scientist

data engineer

data analyst

senior data engineer

financial analyst

data analytics engineer

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>

Data Engineer

Bandit Running

<div>Bandit Running is a pioneering technical performance brand committed to creating innovative, high-quality apparel &amp; gear for goal-driven runners. Our mission to &ldquo;Evolve Running&rdquo; guides everything we do, always putting the needs of the global running community first. As the fastest-growing brand in the sport, we challenge conventional brand-building norms, prioritizing an extremely high-bar for disruptive excellence across product, experiences &amp; content. Our vision is to build an enduring, iconic brand that breaks down barriers &amp; inspires greater passion &amp; participation in the sport we love.
We are seeking a Senior Data Engineer / Analytics Engineer (Contract) to help architect and build the next generation of our backend data systems. This role will partner closely with our Head of Data to design and implement an analytics foundation that powers new models, analyses, KPIs, and AI-driven workflows across the company.
This is a hands-on builder role. You&rsquo;ll be responsible for building reliable, recurring data pipelines, transforming raw data into durable analytical models, and helping shape how Bandit structures data for long-term scalability, including AI-first consumption. 
Requirements 
 
Responsibilities:<ul><li>
Collaborate on and help define Bandit&rsquo;s data architecture, tooling choices, and long-term data strategy.</li><li>
Execute on that strategy by building reliable ELT pipelines into Snowflake using Airbyte out-of-the-box &amp; custom connectors</li><li>
Transform raw source data into clean, well-modeled analytical tables using dbt</li><li>
Translate business context to create enriched data stores from new source tables</li><li>
Build context and semantic layers on top of new data sources to enable self-serve analytics and agentic / AI-driven use cases.</li></ul>
What we&rsquo;re looking for:<ul><li>
5+ years experience in data engineering or analytics engineering roles</li><li>
Expert SQL skills; comfortable modeling complex business logic</li><li>
Experience and opinions on data architecture decisions, tradeoffs, and tooling</li><li>
Good translator of business operations / problems into data schematics</li><li>
AI-oriented data builder</li><li>
Experience working in Snowflake, dbt, data ingestion tools (i.e Airbyte) and Airflow</li></ul> 
Success in this role looks like shipping durable, well-modeled datasets that become the default foundation for analytics, operations and AI-driven workflows across Bandit. 
Benefits 
<ul><li>
Fully Remote</li><li>
~20 hours / week, 12-16 week contract</li><li>
Flexible hours (must be available to meet virtually 1 day / week)</li><li>
$100-150 / hour (depending on location and years of experience)</li></ul> 
At Bandit, we&rsquo;re building an incredible culture rooted in our three core values&mdash;Trust, Empathy, &amp; Excellence. We believe that in order to build the best team, our baseline is an environment where everyone can bring their full &amp; authentic selves to the table. We are committed to fair hiring practices where we hire team members for their potential &amp; advocate for diversity, equity, &amp; inclusion. We do not discriminate based on your race, color, religion, gender identity or expression, sexual orientation, national origin, age, military service eligibility, veteran status, marital status, disability, or any other protected class.</div>

Senior Data Engineer (Contract Position)

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>

Slang AI

<div>
 
 
 Slang AI is redefining customer engagement through conversational AI, making every interaction seamless and efficient. Our mission is to transform the restaurant industry by providing the ultimate voice AI solution for consistently outstanding customer experiences.
 
 
 
 
 
 
 
 At Slang AI, we believe how we build matters just as much as what we build. We foster a culture rooted in hospitality, ownership, and clarity, where every &ldquo;Slangsta&rdquo; feels valued, supported, and connected to the broader impact of our work in the AI-powered future of restaurants.
 
 
 
 
 
 
 Overview
 
 
 
 
 
 We're looking for a
 
 
 
 Data Analytics Engineer
 
 
 
 to join our data team and help build and scale our analytics infrastructure from ingestion to dashboard. You'll build and maintain the pipelines, transformations, and reporting layers that the rest of the company relies on to understand our product, our customers, and our business. This role sits at the intersection of data engineering and BI analytics, and the right person will be equally comfortable writing complex SQL transformations and presenting a clean dashboard to stakeholders.
 
 
 
 
 You'll work closely with product engineering to instrument new features, maintain the business logic behind our core metrics, and keep our data warehouse performant and cost-efficient. There's also real opportunity to push into real-time data infrastructure as the platform evolves, including streaming pipelines and event-driven metric delivery for production services.
 
 
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 
 Build and maintain analytics pipelines in BigQuery using dbt Cloud, including staging, transformation, and mart layers
 
 </li>
 <li>
 
 Manage and configure Airbyte ingestion streams and Hightouch reverse ETL syncs
 
 </li>
 <li>
 
 Partner with product engineering to ensure new features follow our event-driven instrumentation methodology and emit the right data from day one
 
 </li>
 <li>
 
 Define and maintain business logic for metrics construction, serving as the source of truth for how key metrics are calculated
 
 </li>
 <li>
 
 Build, update, and maintain internal dashboards in Looker Studio
 
 </li>
 <li>
 
 Build and maintain BigQuery datasets, views, and scheduled queries
 
 </li>
 <li>
 
 Monitor and optimize query performance and warehouse costs, proactively identifying opportunities to reduce spend
 
 </li>
 <li>
 
 Design and implement data backup and redundancy strategies
 
 </li>
 <li>
 
 Make occasional updates to the customer-facing dashboard layer in the product (TypeScript)
 
 </li>
 <li>
 
 Perform ad-hoc data analysis and produce one-off data pulls for customers as needed
 
 </li>
 <li>
 
 Identify recurring data requests and build automated, self-serve solutions to replace manual fulfillment
 
 </li>
 <li>
 
 Investigate BigQuery continuous queries for publishing metrics to Cloud Pub/Sub, enabling product engineering services to consume analytics data in near real-time
 
 </li>
 <li>
 
 Evaluate Cloud Dataflow for real-time and low-latency data processing use cases as the platform's needs evolve
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 
 5+ years of experience in data engineering, BI analytics, or software engineering
 
 </li>
 <li>
 
 Expert-level SQL skills, particularly in BigQuery or comparable cloud data warehouses
 
 </li>
 <li>
 
 Hands-on experience with dbt (dbt Cloud preferred) for managing transformation pipelines
 
 </li>
 <li>
 
 Experience with data ingestion tools such as Airbyte, Fivetran, or similar
 
 </li>
 <li>
 
 Experience with reverse ETL tools such as Hightouch or Census
 
 </li>
 <li>
 
 Working knowledge of Python for data scripting, automation, and ad hoc analysis
 
 </li>
 <li>
 
 Experience building and maintaining dashboards in Looker Studio or similar BI tools
 
 </li>
 <li>
 
 Strong understanding of event-driven data instrumentation and how analytics contracts should be defined alongside product features
 
 </li>
 <li>
 
 Track record of optimizing data warehouse costs and query performance
 
 </li>
 <li>
 
 Comfort working directly with engineering teams to define data requirements and instrumentation standards
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 Nice to Haves
 
 
 
 <ul>
 <li>
 
 Experience with GCP data services beyond BigQuery (Cloud Dataflow, Pub/Sub, Cloud Functions)
 
 </li>
 <li>
 
 Familiarity with TypeScript or Kotlin
 
 </li>
 <li>
 
 Experience building or contributing to customer-facing analytics features within a product
 
 </li>
 <li>
 
 Prior work with streaming or real-time data architectures
 
 </li>
 <li>
 
 Experience implementing data quality testing frameworks (e.g., dbt tests, Great Expectations, or similar)
 
 </li>
 <li>
 
 Familiarity with data governance practices, including documentation, lineage tracking, and access controls
 
 </li>
 <li>
 
 Experience working at a fast-growing startup where you owned the data stack end to end
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 Location
 
 
 
 
 
 New York City
 
 
 
 
 
 
 
 
 
 
 
 
 
 Compensation &amp; Location
 
 
 
 
 
 
 Compensation for this role is location-based and benchmarked against local market data aligned to the employee&rsquo;s primary work location. Total compensation includes a mix of cash and equity and may vary by location, role level, and experience. Our range is therefore wide and not meant as&nbsp;a negotiation range.&nbsp;
 
 
 
 
 
 
 
 
 
 Our Vision
 
 
 
 
 
 
 Calling a business shouldn&rsquo;t feel like a robot-hostage situation, where you&rsquo;re forced to listen to horrible music and can't reach a human, while enduring a soulless voice uttering "I'm sorry I didn't quite get that" on repeat for eternity. (shudder)&nbsp;
 
 
 That&rsquo;s why we started&nbsp;
 
 
 Slang
 
 
 AI&nbsp;
 
 
 We use the latest AI and audio wizardry to make transacting via voice so enjoyable it&rsquo;s more human than human. By 2030, we will save businesses and consumers 1 billion minutes of precious time while transforming voice channels into the preferred mode of communication (it's faster and easier than text).
 
 
 
 
 We have backgrounds building product at companies like Spotify, Buzzfeed, the New York Times, and OpenTable &mdash;shipping experiences that have reached hundreds of millions of users. Now, we&rsquo;re using our backgrounds to start a new culture, one that puts product and human-centered design above all else while fostering constant learning and growth. Sound like something you&rsquo;d like to be part of? Get on board.
 
 
 
 
 
 
 
 
 
 Our Values&nbsp;
 
 
 
 
 
 
 
 Overachiever Fever.
 
 
 
 &nbsp;We&rsquo;re overachievers (we don&rsquo;t know any other way)
 
 
 
 
 
 Learner Fervor.&nbsp;
 
 
 
 We take every opportunity to learn (especially when it&rsquo;s hard)&nbsp;
 
 
 
 
 
 Humility Ability.
 
 
 
 &nbsp;We approach each other with curiosity and openness (know-it-alls not welcome!)
 
 
 
 
 
 SMB MVP.&nbsp;
 
 
 
 We&rsquo;re an expert member of our customers&rsquo; teams (we earn their trust)
 
 
 
</div>

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
Amazon Web Services (AWS) is a dynamic and rapidly growing business within Amazon and the leader in providing secure, reliable, scalable, and innovative services that help over a million businesses, governments, education, and not for profits across the globe scale and grow! AWS provides a wide set of scalable services to meet customer needs. 
 
At AWS, the Global Deal Strategy and Programs (GDSP) team drives cloud adoption and business growth through innovative pricing strategies. The organization comprises two specialized teams: Strategic Customer Engagements, which guide ** transformative deals with industry leaders, and Private Pricing Programs &amp; Experiences, which scales and optimizes pricing solutions across our diverse customer base. Within GDSP, you will develop deep expertise in cloud economics, hone your strategic thinking, and directly impact AWS's market leadership while working with latest technologies and global clients. 
 
The AWS Global Deal Strategy and Programs (GDSP) organization is responsible for the Private Pricing Program. The Private Pricing Analytics and Insights (PPA&amp;I) team owns building scalable analytical solutions that enable the GDSP organization with actionable insights to make data-driven decisions. This role will focus on Data Engineering, and Analytics related to the Private Pricing Program, requiring deep technical skills, strong business acumen and a deep analytical background to provide actionable data-driven insights and decision support. 
 
As a Data Engineer on this team, you will drive efficiency in data handling processes, setup product analytics, drive advanced analysis and build new metrics which are key inputs to improve the health, scale and growth of the Private Pricing Program. You will work collaboratively with the business leaders operations, and engineering teams on many non-standard and unique business problems and support business initiatives by collecting required and related data from external/internal sources. 
 
The ideal candidate should have strong communication skills and ability to prioritize effectively to ensure timelines are met. You will own projects from engaging with customers to production and delivery of a suite of tools used by the organization to make key business decisions. You should be a self-starter, comfortable with ambiguity, able to think big and be creative (while still paying careful attention to detail). You think in terms of architecture, not just code. You proactively work to improve the consistency and integration between your team&rsquo;s BI solutions and any related systems or artifacts. 
 
Key job responsibilities 
Design, develop, and maintain scalable data solutions for metrics, reports, analyses, and dashboards that support analytical and business needs 
 
Collaborate with technology teams to extract, transform, and load data from diverse sources using AWS services and internal tools 
Build and deliver high-quality datasets that support data science initiatives and customer reporting requirements 
 
Automate and optimize reporting processes to enable self-service analytics for stakeholders 
Translate business problem statements into technical analysis requirements 
 
Apply analytical and statistical rigor to answer business questions and drive data-driven decisions 
Develop measurement frameworks that quantify customer experience and drive business outcomes 
 
Create queries and visualizations for ad-hoc requests, projects, and ongoing reporting needs 
Write efficient, optimized queries with deep knowledge of data structures and query optimization techniques 
 
Adopt best practices in reporting and analysis including data integrity, design, validation, and documentation 
 
Troubleshoot operational data quality issues and audit existing data pipelines and queries 
 
Recommend improvements to back-end data sources for increased accuracy and simplicity<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of data engineering experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience</li><li>1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience</li><li>Experience with data modeling, warehousing and building ETL pipelines</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions</li><li>Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
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. 
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. 
USA, NY, New York - 145,300.00 - 196,600.00 USD annually 
USA, TX, Austin - 132,100.00 - 178,800.00 USD annually 
USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually</div>

Data Engineer, AWS GDSP A&I

Outfront Media

<div>Job Summary
At OUTFRONT Media, a leader in Digital Out of Home (DOOH) advertising, we are blending cutting-edge technology with our nationwide network of digital billboards and transit displays to create innovative solutions that push the boundaries of what is possible. We are looking for a passionate and experienced Senior Data Engineer to join our growing Data &amp; Analytics team.
This role is designed for a senior-level data professional with deep expertise in data engineering and strong business intelligence experience. The right candidate will build and scale modern data pipelines, design reliable and performant data models, and enable the business through high-quality dashboards and self-service reporting. This is a hybrid role grounded in data engineering first, with a clear expectation that the individual can also deliver business-facing analytics solutions in Sigma Computing.
As a Senior Data Engineer, you will leverage your expertise in cloud technologies, data architecture, and modern data warehouses to design and implement scalable, high-impact solutions that drive real business results. You will partner with leadership and stakeholders across the business to ensure our data systems evolve alongside company needs, while also helping deliver trusted dashboards and reporting assets that support smarter decision-making.
What You'll Do<ul><li>Build and maintain high-performance data pipelines that enable deeper analysis, reporting, and insights across the business.</li><li>Design and implement scalable data models and warehouse structures that support analytics, reporting, and data science needs, optimizing for speed, reliability, and maintainability.</li><li>Create seamless data ingestion and transformation processes using modern ETL/ELT practices, leveraging AWS, Snowflake, dbt, and Fivetran to ensure smooth and reliable data flow.</li><li>Own and improve the backend data foundation that powers dashboards, reporting, and self-service analytics.</li><li>Collaborate with business teams to understand data and reporting needs, and translate them into flexible, scalable technical solutions.</li><li>Develop and maintain dashboards, reports, and analytic views in Sigma Computing, ensuring business users have access to trusted, actionable, and easy-to-use insights.</li><li>Partner with stakeholders to define KPIs, business logic, and reporting requirements, and translate them into scalable data models and reporting solutions.</li><li>Establish best practices for data quality, governance, documentation, and reporting consistency across both engineering and analytics workflows.</li><li>Continuously improve reporting and analysis by automating processes, streamlining workflows, and empowering teams with self-service data tools.</li><li>Operate effectively within Agile delivery processes, contributing to sprint planning, backlog refinement, estimation, story development, and cross-functional execution using Jira and Confluence.</li></ul>
Experience<ul><li>7+ years of experience designing and implementing modern data warehouse and analytics engineering solutions, with a focus on scalability, reliability, and performance.</li><li>7+ years of experience writing advanced SQL and developing robust ETL/ELT pipelines to transform and integrate data across multiple systems.</li><li>7+ years of experience using Python or similar languages to build scalable, efficient, and maintainable data solutions.</li><li>Strong hands-on experience with AWS, Snowflake, dbt, Fivetran, and Sigma Computing.</li><li>Experience building and optimizing data models in Snowflake and managing transformation workflows in dbt.</li><li>Experience using Fivetran or similar ingestion tools to build and maintain reliable source-to-warehouse pipelines.</li><li>5-7 years of dashboarding and BI experience overall, with strong hands-on experience delivering reporting solutions for business users.</li><li>Hands-on Sigma Computing experience is required. Ideal candidates will have 5-7 years of Sigma Computing experience; at minimum, candidates must have 3+ years of direct Sigma Computing experience, along with prior experience using Tableau and/or Power BI.</li><li>Proficient in cloud technologies, especially AWS, and experienced in building scalable data solutions in cloud-native environments.</li><li>Experience working in Agile teams and collaborating across engineering, analytics, and business stakeholders.</li><li>Strong working knowledge of Jira and Confluence for backlog management, sprint planning, documentation, and team collaboration.</li></ul>
Technical Expertise<ul><li>Deep expertise in modern data engineering and analytics engineering practices.</li><li>Strong hands-on experience with AWS, Snowflake, dbt, Fivetran, and Sigma Computing.</li><li>Expertise in building and optimizing data models, transformations, and reporting-ready datasets in Snowflake and dbt.</li><li>Strong hands-on experience delivering business-facing dashboards and self-service reporting in Sigma Computing, supported by well-modeled, scalable data structures in Snowflake and dbt.</li><li>Prior experience with Tableau and/or Power BI is preferred.</li><li>Strong understanding of data modeling, semantic layer design, and self-service analytics enablement.</li><li>Solid understanding of data governance, data quality, and documentation best practices.</li><li>Deep knowledge of identity management, data privacy, audience targeting, cross-device graphs, and related technologies.</li><li>Solid understanding of digital advertising technology, including ad serving, analytics, DSP, DMP, SSP, QA, and targeting.</li></ul>
Soft Skills<ul><li>Strong cross-functional collaboration skills, with experience aligning technical and business stakeholders on priorities and trade-offs.</li><li>Exceptional communication skills, capable of breaking down complex technical concepts for non-technical audiences.</li><li>Strong business acumen and an analytics mindset, with the ability to move from raw data to meaningful recommendations.</li><li>Ability to operate across both backend engineering and front-end analytics use cases.</li><li>Strong organizational and delivery skills, with the ability to work effectively in Agile teams and manage multiple priorities.</li></ul>
Education
Bachelor of Engineering in Computer Science or equivalent experience preferred.
The salary range for this role is $165,000-$185,000 per year. Compensation is determined during our interview process by assessing a candidate&rsquo;s experience and skills relative to internal peers and market benchmarks evaluated for the scope and responsibilities of the position. 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 and New Jersey Salary Transparency Law.<h3 class="jobSectionHeader">
To all Recruitment Agencies: OUTFRONT Media LLC does not accept agency and unsolicited resumes. Please do not forward resumes to our OUTFRONT Media employees or any other company location.</h3>
OUTFRONT Media is not responsible for any fees related to unsolicited resumes.
OUTFRONT Media Is An Equal Opportunity Employer
All applicants shall receive equal consideration without regard to race, color, religion, gender, marital status, gender identity or expression, sexual orientation, national origin, age, veteran status or disability. Please refer to the OUTFRONT Media Affirmative Action policy statement.</div>

Senior Data Engineer

Honeycomb Insurance

<div>
 
 Honeycomb
 
 
 
 At Honeycomb, we're not just building technology, we&rsquo;re reshaping the future of insurance.
 
 
 In 2025, Honeycomb was recognized by Dun &amp; Bradstreet as &ldquo;Top 10 Best Start Up Companies to Work For&rdquo; in Israel and named by LinkedIn as &ldquo;Top 10 Startups in Chicago&rdquo;.
 
 
 How did we earn these honors?
 
 
 Honeycomb is a rapidly growing global startup, generously backed by top-tier investors and powered by an exceptional team of thinkers, builders, and problem-solvers. Dual-headquartered in Chicago and Tel Aviv (R&amp;D center), and with 5 offices across the U.S., we are reinventing the commercial real estate insurance industry, an industry long overdue for disruption. Just as importantly, we ensure every employee feels deeply connected to our mission and one another.
 
 
 With over $55B in insured assets, Honeycomb operates across 20+ major states, covering 60% of the U.S. population and increasing its coverage.
 
 
 If you&rsquo;re looking for a place where innovation is celebrated, culture actually means something, and smart people challenge you to be better every day - Honeycomb might be exactly what you&rsquo;ve been looking for.
 
 
 
 About Us
 
 
 
 Honeycomb Insurance is a modern, data-driven insurance company building smarter ways to underwrite and manage risk.
 
 
 
 About The Role
 
 
 
 We are looking for a Financial &amp; Data Analyst to join our Finance organization and help us build a scalable, accurate, and automated data foundation. This role bridges Finance, Accounting, and Engineering, ensuring that the data powering our financial models, carrier reporting, billing systems, and management reporting is clean, reliable, and engineered for growth.
 
 
 If you enjoy owning data pipelines end-to-end, solving messy data problems, and enabling business teams to move beyond spreadsheets, this is an opportunity to make a major impact.
 
 
 
 Location: Chicago or New York
 
 
 
 Reporting to: Chief Financial Officer
 
 
 
 What You&rsquo;ll Do
 
 
 
 
 Data Engineering &amp; Pipeline Development
 
 
 
 <ul>
 <li>
 Partner with finance and operations teams to understand their data needs and translate them into reliable data models.
 </li>
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 Partner with Engineering to validate, QA, and reconcile data from policy admin systems, billing systems, and operational databases.
 </li>
 <li>
 Build and maintain automated pipelines supporting Finance and Accounting (SQL, Python, dbt, or similar tools).
 </li>
 <li>
 Develop data models that make financial and operational data reliable, accessible, and well-structured.
 
 
 </li>
 </ul>
 
 Fronting Carrier &amp; Regulatory Reporting
 
 
 
 <ul>
 <li>
 Own the data preparation for monthly reports to insurance partners.
 </li>
 <li>
 Ensure data completeness, accuracy, and alignment across sources (policy, claims, billing, accounting).
 
 
 </li>
 </ul>
 
 Billing System Data Preparation &amp; Cleansing
 
 
 
 <ul>
 <li>
 Support a billing system migration/implementation by cleaning, reconciling, and validating large datasets.
 </li>
 <li>
 Work closely with Engineering and Finance to align data with billing schemas and business rules.
 
 
 </li>
 </ul>
 
 Analytics Support for FP&amp;A and Accounting
 
 
 
 <ul>
 <li>
 Create data assets enabling self-service dashboards and analytical tools.
 </li>
 <li>
 Monitor the data and ensure strong data integrity.
 </li>
 <li>
 Investigate data anomalies and help Finance understand operational drivers behind performance metrics.
 
 
 </li>
 </ul>
 
 Required
 
 
 
 
 What You Bring
 
 
 
 <ul>
 <li>
 3+ years of experience as a Data Engineer, Analytics Engineer, BI Engineer, or similar role.
 </li>
 <li>
 Strong SQL and Python skills and experience working with relational databases.
 </li>
 <li>
 Experience with a cloud data warehouse &mdash; BigQuery preferred
 </li>
 <li>
 Experience building ETL/ELT pipelines (e.g., dbt, Airflow, Fivetran, custom pipelines).
 </li>
 <li>
 Comfort working with messy data, performing cleansing, reconciliation, and QA.
 </li>
 <li>
 Analytical mindset with strong attention to detail
 </li>
 <li>
 Ability to communicate findings clearly to non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience in insurance, fintech, or financial services.
 </li>
 <li>
 Experience supporting data-driven processes in Finance, FP&amp;A, Accounting, or similar business functions.
 </li>
 <li>
 Familiarity with financial systems such as ERPs or billing systems.
 </li>
 <li>
 Experience with BI tools like Looker, Power BI and Tableau.
 </li>
 <li>
 Experience leveraging AI to generate SQL and Python scripts.
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 You&rsquo;re a builder who enjoys creating structure in ambiguity.
 </li>
 <li>
 You&rsquo;re the type who spots data issues before anyone else does &mdash; then digs until you find the root cause.
 </li>
 <li>
 You love empowering non-technical teams with accurate, reliable data.
 </li>
 <li>
 You thrive in cross-functional work between Finance, Accounting, and Engineering.
 </li>
 <li>
 This role is open to candidates based in New York or Chicago, IL
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Salary: $120,000-$170,000
 </li>
 <li>
 ISO stock options
 </li>
 <li>
 Medical, dental, and vision coverage for you and your dependents
 </li>
 <li>
 HSA with company contributions
 </li>
 <li>
 401(k) (non-matching)
 </li>
 <li>
 Flexible time off
 </li>
 <li>
 10 company-paid holidays
 </li>
 <li>
 Paid family leave
 </li>
 </ul>
</div>

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