Kit is an email-first operating system for creators who mean business. We help creators grow and monetize their audience with ease. For coaches, YouTubers, authors, podcasters, and other creatives, there isn't a better marketing hub to rely on to grow audiences, automate email marketing, and sell digital products — all within one platform. More importantly, there isn't a team more committed to helping creators earn a living. We're on a mission to help creators earn $1 billion using our creator marketing platform. We have always been 100% independent and 100% remote. We are proud to have built a product that our customers love, and we look for people who have enthusiasm and belief in our mission, vision, and values to join our team. We're also embracing AI thoughtfully — both in how we build and how we hire to ensure our team is adaptable, innovative, and ready for what's next. The role Kit is at an inflection point. We have the product, the customers, and the mission — but our ability to make fast, confident decisions across Finance, Product, Marketing, and Revenue is still bottlenecked by an analytics layer that hasn't kept pace with the business. We're hiring a Lead Analytics Engineer to solve for that: to build the canonical data foundation that lets every team at Kit operate from a single source of truth, and to raise the bar for how data work gets done across the entire function. This is a full-time IC role for someone who thinks in systems, communicates in writing, and finds genuine satisfaction in turning ambiguous metric definitions into reliable, well-documented truth. The success of this role is measured by whether the rest of the company can confidently explore data without depending on the Data team for routine interpretation. Your support system You’ll report to Samuel Umachi, Head of Data, and collaborate closely with an analytic engineer, infrastructure engineers, and cross-functional partners in Product, Engineering, Finance, Marketing, Sales, and Creator Growth. You’ll partner directly with stakeholders who rely on the Reporting Hubs you’ll help build and maintain. What you'll do - First Week: Complete onboarding in Notion and meet your teammates through Get-To-Know-You calls. Get oriented in our core tools: dbt, Github, Redshift, Omni, Slack, and Linear. Start reading existing documentation on our Reporting Hub architecture and canonical metric definitions. - First Month: Audit active Reporting Hub models across Finance, Marketing, Sales, Product Strategy, and Creator Lifecycle. Map current churn logic implementation and identify inconsistencies in canonical metric definitions. Assess Redshift performance strain areas and flag fragile model dependencies. Publish a written architectural assessment memo with your initial findings and recommended priorities. Serve as the data team’s voice in cross-functional discussions about metric definitions, attribution logic, and analytical rigor across Finance, Product, and Marketing. - First Six Months: Propose and begin executing a 6–12 month modernization roadmap for our modeling layer. Refactor the highest-risk models across all business verticals Clarify attribution model contracts and improve cross-functional documentation standards. Measurably reduce warehouse inefficiencies through distribution and sort key optimization, not infrastructure scaling. Improve Segment event modeling structure and align event design with reporting needs in partnership with Product and Engineering. Drive company-wide adoption of canonical metrics by working directly with functional leads to replace ad hoc definitions with documented, auditable standards. - First Year: Complete the Reporting Hub foundation across business verticals with canonical metric consistency enforced. Enable true stakeholder self-serve, so teams can explore data without relying on the Data team for routine questions. Reduce model rework caused by upstream ambiguity through upstream design patterns and documentation. Raise the overall modeling sophistication of the Data team through mentorship, standards, and shared tooling. Leadership makes resource allocation and growth decisions using a shared metric layer they trust without qualification. Finance closes faster because revenue and subscription models are reliable and consistent. Product and the broader company make decisions with cohort and performance data they no longer need to manually verify, allowing the data team to ship faster with less rework. What will S.E.T. you up for success Skills - Deep SQL mastery. You write queries that are readable, performant, and designed for maintainability. You understand relational semantics deeply, including join selection, cardinality management, and predicate placement. - Redshift expertise. You know how sort keys, distribution styles, concurrency, vacuum, and analyze behavior work, and how to design around their constraints. - dbt fluency. You build modular, well-documented, refactorable dbt code. You have opinions about macro design, test strategy, and what “good” looks like in a dbt project at scale. - Business modeling strength. You can translate revenue recognition logic, attribution frameworks, funnel stages, and lifecycle metrics into reliable, auditable models that stakeholders trust. - Written communication. You write clear architectural memos, modeling documentation, and decision rationale. You communicate trade-offs, not just conclusions. - Analytical judgment. You have experience navigating contested metric definitions, challenging dashboard results, or attribution debates while maintaining analytical rigor. - Stakeholder translation. You can explain complex metrics and modeling decisions to different stakeholders and communicate in terms they trust. Experiences - 7–10+ years working in analytics engineering, data engineering, or a closely related role, with at least a few years operating at a senior or staff level. - Designed or significantly refactored a warehouse modeling layer in a production environment. - Built or stewarded canonical metric definitions in a multi-stakeholder environment. - Worked in a SaaS company where revenue recognition, churn logic, or subscription modeling was a core part of the work. - Experience with product analytics modeling, Segment event architecture, identity resolution, or cohort/retention modeling is a strong plus. - Collaborated with infrastructure engineers to address performance challenges at the warehouse level. Traits - As a lead level IC, you see your role as amplifying the effectiveness of the entire data team and driving company wide impact. You lead by example. - You think in systems. When you look at a modeling problem, you see the upstream causes and downstream consequences, not just the immediate fix. - You’re patient with complexity. You don’t oversimplify hard problems, and you don’t ship a definition you can’t defend. - You document as you go, not as an afterthought. You believe that work that’s not written down didn’t really happen. - You push back when necessary. You’re comfortable disagreeing with stakeholders, explaining your reasoning, and holding the line on rigor when speed would create long-term problems. - You use AI tools actively. You’re comfortable using AI to accelerate drafting, exploration, and deployment, while applying your own judgment to the outputs. - You operate with extreme autonomy. At a Staff level, you don’t wait for a detailed brief. You identify what needs to be done, communicate your plan, and move. What won't set you up for success - Defaulting to infrastructure scaling when the real problem is modeling design. - Preferring to build tools or processes before understanding the business context they’re meant to serve. - Optimizing in isolation, without documenting decisions, communicating trade-offs, or looping in collaborators. - Discomfort with ambiguity. Many of our metric definitions are still evolving. You’ll need to lead the process of resolving them, not wait for resolution before acting. - A preference for being told what to build rather than helping define what should be built. Working hours and location We’re 100% remote with team members across the globe. We work mostly on East Coast time, so if you’re based on the West Coast of the United States, Europe, or Asia, you might have a few early mornings or late evenings. We do our best to keep things reasonable, but a little time zone juggling comes with the territory. Compensation + perks + benefits Kit has standardized salaries based on position, no matter where you live. For this role, we’re hiring at our level 5 ($198,000). Level is determined based on experience and our interview process. Perks + benefits include: - Profit Sharing - Kit equity - 401k with a 5% match - We cover up to $2,100 per month toward medical premiums, with dental and vision premiums fully covered. We offer Health Insurance plans through Aetna - $2,000 equipment allowance for your first two years, $1,000 budget every following two years. Company-provided laptops are issued to every Kit team member and are not included in the equipment budget - Individual learning + development budget ($3,500/year) - Gender affirming benefits - Childcare benefit up to $3,000 annually - Twenty (20) days of paid time off during each year of employment - Paid paid vacation: An after-tax bonus of $1,000 for taking five consecutive days of vacation where you’re fully unplugged from work - Ten (10) paid holidays a year - Two weeks of paid sick time each year, including mental health + well being days - Twelve (12) weeks paid parental leave and flexible scheduling in your child’s first year - Up to six weeks of paid bereavement leave, medical leave, and disaster after six months of employment, two weeks of each paid leave in your first six months - Winter Break Closure: Kit closes for a week at the end of December, giving everyone a collective break to enjoy the holiday season. Essential support services remain available, with teams coordinating to ensure coverage during this period - Four-week, paid sabbatical after five years with the team - Fantastic in-person or virtual retreats with the team twice a year How to apply We usually receive a large number of applications, and our goal is to follow up with you within two weeks. You’ll hear from us either way. Here’s what you can expect from the rest of our hiring process: - A phone screen with our recruiter - Hiring manager interview - Take-home assignment / Architectural case study - Technical interview - Final alignment call We’ll keep you informed through every step. To get started, complete this application, including a cover letter and answers to the questions on the next page. We read every single application, and your cover letter and responses help put your experience into context. Kit is an equal opportunity employer We value diversity in all of its forms. Research tells us that applicants who are female or non-binary, as well as applicants who are people of color, are less likely to apply for roles they do not feel 100% qualified for. If you think you meet more than 50% of our requirements but fewer than 100% of them, please apply. We’re imperfect communicators, so think of our job postings as the starting point for discussion rather than proof that you shouldn’t apply. Kit does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.

• Complete onboarding in Notion and meet your teammates through Get-To-Know-You calls. Get oriented in our core tools: dbt, Github, Redshift, Omni, Slack, and Linear. Start reading existing documentation on our Reporting Hub architecture and canonical metric definitions. • Audit active Reporting Hub models across Finance, Marketing, Sales, Product Strategy, and Creator Lifecycle. Map current churn logic implementation and identify inconsistencies in canonical metric definitions. Assess Redshift performance strain areas and flag fragile model dependencies. Publish a written architectural assessment memo with your initial findings and recommended priorities. Serve as the data team’s voice in cross-functional discussions about metric definitions, attribution logic, and analytical rigor across Finance, Product, and Marketing. • Propose and begin executing a 6–12 month modernization roadmap for our modeling layer. Refactor the highest-risk models across all business verticals Clarify attribution model contracts and improve cross-functional documentation standards. Measurably reduce warehouse inefficiencies through distribution and sort key optimization, not infrastructure scaling. Improve Segment event modeling structure and align event design with reporting needs in partnership with Product and Engineering. Drive company-wide adoption of canonical metrics by working directly with functional leads to replace ad hoc definitions with documented, auditable standards. • Complete the Reporting Hub foundation across business verticals with canonical metric consistency enforced. Enable true stakeholder self-serve, so teams can explore data without relying on the Data team for routine questions. Reduce model rework caused by upstream ambiguity through upstream design patterns and documentation. Raise the overall modeling sophistication of the Data team through mentorship, standards, and shared tooling.

Role Description Cardinal Technology Systems Corp. is currently seeking a Jr. Data Analytics Engineer to work for our company. - Must possess IT-I security clearance or have a current National Agency Check with Local Agency Check and Credit Check (NACLC). - Design, build, and deploy robust enterprise-level reports, dashboards, and data visualizations using our primary business intelligence (BI) platform such as SAP Business Objects or similar BI tools. - Collaborate with data engineering to leverage dimensional models, including fact tables and dimensions tables (star/snowflake schemas), for intuitive and performance reporting. - Write complex, highly optimized SQL queries against our Oracle and Databricks environments to extract and aggregate the data needed for reporting applications. - Partner with business analysts and key stakeholders to gather requirements, translate business needs into technical specifications, and ensure reporting solutions deliver actionable insights. - Proactively monitor, analyze, and optimize the performance of reports and underlying queries to ensure a fast, reliable, and seamless user experience across the enterprise. - Leverage core AWS services (e.g. S3, EMR, Redshift, Glue) to deliver cloud-native reporting solutions. - Manage the full lifecycle of reporting assets, including documentation, version control, scheduled refreshes, and providing ongoing support and enhancements. Qualifications - Bachelor's degree in computer science or related engineering field. - 1+ years of hands-on experience with SQL programming. - 1+ years of experience with at least one major BI platform (e.g. PowerBI, Tableau, Qlik). - Experience with performing data analysis and interpreting results. - Conceptual understanding of data warehousing concepts and dimensional modeling, including a clear ability to articulate the difference and use cases for star vs. snowflake schemas. - Demonstrated experience developing scripts or applications using Python is preferred. - High level of self-motivation, willingness to learn new technologies and work in a distributed team environment. - The person in this position needs to occasionally move about inside the office to access file cabinets, office machinery, or to communicate with co-workers, management, and customers, which may involve delivering presentations. Requirements - Must possess IT-I security clearance or have a current National Agency Check with Local Agency Check and Credit Check (NACLC). Preferences - 1+ years of experience in dedicated reporting, business intelligence, or data analytics role. - Experience developing reports and running queries within a Databricks environment (using notebooks, SQL Warehouses, etc.). - Familiarity with navigating the AWS ecosystem, specifically with services related to data storage and access like S3 and IAM. - AWS Certification (e.g. AWS Certified Data Analytics – Specialty or Solutions Architect). - Proficiency in a scripting language, particularly Python (Pandas, Pyspark) for data manipulation or automation. - Strong communication skills with ability to present technical findings to non-technical stakeholders. Benefits - Medical, Dental, Vision Benefits - Paid Life - Paid Vacation, Holidays, Sick Leave, Floating Holidays, Bereavement Leave - Semi-monthly pay cycle

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are interested in developing long-term relationships with superior instructors who have high professional standards, excellent communication skills, enthusiasm, and a commitment to providing the finest practitioner-focused education. We are seeking primarily Industry Professionals to share their knowledge and experience with undergraduate and graduate students in a variety of fields. - Primary responsibilities will include course development for new course offerings and redevelopment of current courses to incorporate latest technologies, update course material, and address industry trends. - Potential instructional opportunities to teach in area(s) of expertise in the online learning environment. - Courses meet once or twice a week for eight weeks. - Faculty are responsible for facilitating student learning by teaching educational courses and programs in accordance with DeVry University requirements. - Faculty develop course syllabi and lesson plans and apply teaching techniques to best achieve course and programmatic objectives. - All DeVry instructors will participate in a comprehensive faculty training program and ongoing faculty development activities to ensure the highest quality instruction. - DeVry University does not guarantee any specific number of work hours or assignments, which may vary based on the University’s needs and discretion. - Act as subject matter expert in area of business analytics to develop and review course material, following the guidance set forth by the curriculum dean, including course objectives, syllabus, assignments, lessons, and projects. - Communicate regularly with the curriculum dean and instructional design team throughout the curriculum development process through email and virtual conferencing. - Collaborate with the instructional design team to present course material in a manner that will provide students with the best classroom experience. - Identify and integrate appropriate course instructional technologies into course design. - Model effective verbal and written communication to teach in a manner that engages the students, provides clarity, and improves student learning. - Ensures that all course content, including assignments and discussions, align to course objectives. - Completes other duties as assigned. Qualifications - Doctorate degree in Financial Analytics, Statistics, Database Management, Market Research, Qualitative Research Methods, Applied Computer Science, Information Security, or out-of-field doctorate with a minimum of 15 graduate course credit hours in Financial Analytics, Statistics, Database Management, Market Research, Qualitative Research Methods, Applied Computer Science, Information Security, or related discipline. - Proficient in data analysis software such as Power Bi, SQL, R, Python, Tableau, Alteryx, and advanced Excel add ons. - Additional requirements driven by state licensing or accreditation considerations may apply. - Faculty must have requisite subject matter expertise and outstanding communication skills. - *Please upload a copy of your unofficial transcripts graduate level and above. Requirements - Visiting Professor pay is based on degree, credit hours taught per 8-week session, and location. - Pay may vary in most states from $1500-$2700 per 8-week session. - Pay in the states of AZ, CA, IN and PA is paid at an hourly rate of either $22.00/hour or $23.50/hour. - Curriculum development pay may vary from $1500-$3000 per course development or redevelopment. Benefits - 401(k) and Roth Plan - Paid Tuition Program - Remote and Flex Work Options - Paid Sick Time - Technology Stipend - Benefits vary based on employment status. Part-time/Visiting Professors positions may not be eligible for all benefits.