data engineer

software engineer

data scientist

financial analyst

data analyst

analytics engineer

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>

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>
 <li>
 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>

Data Analyst

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>

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

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>

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

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Rapid &amp; Rural Logistics (R2L) team is seeking a Business Intelligence (BI) Engineer to join the Analytics Team. The R2L team, which includes Sub Same Day (SSD), covers a portfolio of high-growth businesses with unique fulfillment and operational capabilities. R2L exists solely to meet the goal of quick, accurate delivery, which is constantly being challenged and changed as we adapt to our customer demands and make improvements. To meet this goal, R2L must remain flexible at all times, adapting to all changes and growth that come our way. As a Business Intelligence (BI) Engineer, your focus will be on providing metrics, operational insights, and other analytical support to stakeholders for the Sub-Same Day (SSD) Delivery business. The Delivery BI team partners closely with Delivery and operations teams to influence the strategic direction of the business, drive operational excellence, and make sound investment and expansion decisions, with the primary goal of continuously improving the customer experience while driving long-term profitability for our portfolio of businesses. We experiment constantly, fail fast, and never stop learning. 
 
The ideal candidate will draw upon advanced analytical and problem-solving skills, along with a passion for building solutions for automated operational management. The successful leader of this team will collaborate effectively with internal end-users, cross-functional stakeholders, and technical teams to enable data-driven decision-making. They must be a self-starter, show strong bias for action, be comfortable with ambiguity, and be able to think big and be creative to support a rapidly growing business. They will provide technical and business expertise in integrating data from various source systems and presenting it through an array of self-service applications. We look for candidates who are excellent communicators, inspiring leaders, self-motivated, flexible, hardworking, and who like to have fun. If you are excited about data, are results-oriented, and want to join a growing analytics team, this role is for you. 
 
Key job responsibilities 
The successful candidate is a seasoned data professional with a strong bias for action, data modeling, proficiency with data visualization tools, ETL, SQL, and scripting skills. In this role, you will help identify complex business problems, recognize opportunities, and implement solutions to improve operations and finance-facing systems, processes, and tools. The successful candidate will provide technical expertise in extracting, integrating, and analyzing critical data, clearly communicate any potential discrepancies and/or reporting downtime, including specific root causes and steps to resolution, and design and develop key performance metrics and indicators. The successful candidate will be a self-starter, quick learner, comfortable with ambiguity, results-oriented with strong attention to detail, insist on high standards, and adapt to a rapidly evolving environment. A typical day in this role provides an opportunity to build innovative data solutions with large-scale systems, identify high-priority work and projects that maximize results for key stakeholders, and solve complex problems that impact company-wide strategic decisions. Further, you will help automate processes by developing deep-dive tools, metrics, and dashboards to communicate these insights in real-time to business teams. Successful members of this team collaborate effectively with business customers and cross-functional data management teams to solve problems and implement new solutions. 
 
A day in the life 
A typical day in this role provides opportunities for building innovative solutions with large-scale data tools, identifying high-priority work and projects that maximize results for key stakeholders, and solving complex problems that impact company-wide strategic decisions. 
<ul><li>Take detailed requirements from stakeholders to deeply understand their current manual processes and pain points</li><li>Think creatively to identify opportunities to solve problems using technology-driven solutions</li><li>Design and implement optimal automation solutions to address stakeholder needs</li><li>Respond to ad hoc requests and provide support as needed</li><li>Thoroughly document all processes, solutions, and learnings to ensure knowledge capture and sharing</li></ul> 
About the team 
The Rapid and Rural Logistics team covers a portfolio of high-growth businesses with unique fulfillment and operational capabilities such as Sub Same Day (SSD). Our team needs to move fast and scale quickly with the growing businesses we support. We expect you to be able to identify one- vs two-way doors and make decisions on your own, requesting help when necessary. Strong bias for action is important. Technical skills must be balanced against people skills and business acumen so you can work with stakeholders to understand their needs and deliver the optimal BI solution.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field</li><li>3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience</li><li>Experience with data visualization using Tableau, Quicksight, or similar tools</li><li>Experience writing complex SQL queries</li><li>Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling</li><li>Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience working directly with business stakeholders to translate between data and business needs</li><li>Experience managing, analyzing and communicating results to senior leadership</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 - 109,500.00 - 185,000.00 USD annually 
USA, WA, Bellevue - 99,500.00 - 160,000.00 USD annually</div>

Business Intelligence Engineer, R2L Analytics

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