MediaRadar, Inc.

• Build and operate pipelines: Design, build, and optimize robust ETL/ELT pipelines that move and transform millions of daily data points reliably and efficiently. • Work hands-on with the open-source stack: Build and maintain production data workflows using tools such as dbt, ClickHouse, and open-source orchestration frameworks (Airflow, Dagster, or similar). • Engineer and tune databases: Write and optimize complex SQL across SQL Server and Postgres — schema design, indexing, performance tuning, query optimization, and root-cause analysis. • Support platform modernization: Contribute to the hands-on migration away from Azure Databricks toward a more open, flexible, AWS-based stack, minimizing disruption to high-volume daily data delivery. • Prototype and evaluate: Help build proofs-of-concept to benchmark new tools and patterns, and feed clear results back into the team’s adoption decisions. • Work with AI-assisted tooling: Use AI coding assistants and well-crafted prompts (e.g., GitHub Copilot, Claude, ChatGPT) to accelerate pipeline development, SQL generation, debugging, testing, and documentation — always reviewing and validating the output before it ships. • Safeguard data quality and reliability: Implement testing, validation, monitoring, observability, and CI/CD practices so data stays accurate and pipelines stay healthy at scale. • Integrate across systems: Understand the systems upstream and downstream of your pipelines, from ingestion through to client-facing platforms, to ensure clean, end-to-end data delivery. • Collaborate across a distributed team: Partner with engineers in North America and India, participate in code reviews, and learn the nuances of the Advertising and Market Research domain.

• Provide timely and accurate responses to customer inquiries and technical issues via email, chat, and phone. • Troubleshoot and resolve technical problems related to MediaRadar’s suite of products. • Ensure all support tickets are resolved in a timely manner, adhering to SLAs (Service Level Agreements). • Serve as the point of contact between clients and internal teams (Customer Success, Product, Engineering) to escalate and resolve complex issues. • Maintain clear and concise documentation of customer interactions and resolutions within the CRM (Salesforce.com). • Identify recurring customer issues and collaborate with cross-functional teams to address root causes. • Document and update support processes to improve efficiency and customer satisfaction. • Gather and report customer feedback to the Product and Engineering teams for continuous product improvement. • Work closely with the North American Customer Success team to ensure a seamless client experience. • Communicate effectively with clients, providing updates and solutions on technical issues and product queries. • Participate in regular team meetings to stay aligned on ongoing client needs and support initiatives.

Role Description As a Client Support Specialist, you will be a key player in delivering exceptional service to MediaRadar's North American clients. You will handle technical support inquiries, troubleshoot issues, and ensure timely resolution. This role demands strong communication skills, technical acumen, and the ability to work efficiently in EST hours to support our North American client base. Key Responsibilities - Provide timely and accurate responses to customer inquiries and technical issues via email, chat, and phone. - Troubleshoot and resolve technical problems related to MediaRadar’s suite of products. - Ensure all support tickets are resolved in a timely manner, adhering to SLAs (Service Level Agreements). - Serve as the point of contact between clients and internal teams (Customer Success, Product, Engineering) to escalate and resolve complex issues. - Maintain clear and concise documentation of customer interactions and resolutions within the CRM (Salesforce.com). - Identify recurring customer issues and collaborate with cross-functional teams to address root causes. - Document and update support processes to improve efficiency and customer satisfaction. - Gather and report customer feedback to the Product and Engineering teams for continuous product improvement. - Work closely with the North American Customer Success team to ensure a seamless client experience. - Communicate effectively with clients, providing updates and solutions on technical issues and product queries. - Participate in regular team meetings to stay aligned on ongoing client needs and support initiatives. Qualifications - 3+ years of experience in a customer support role, preferably within a SaaS, technology, or ad-tech environment. - Strong problem-solving skills and the ability to troubleshoot complex technical issues. - Excellent communication skills in English (both written and verbal) with the ability to explain technical information clearly. - Experience with CRM tools such as Salesforce and similar platforms. - Ability to work Eastern Standard Time (EST) hours to support North American clients. - Strong organizational skills with a customer-first mindset. Preferred Qualifications - Experience working with North American clients in a support or technical troubleshooting capacity. - Familiarity with the advertising technology or SaaS-based products. - Experience providing technical support for B2B clients and working in a fast-paced environment.

• We are looking for a highly technical, hands-on Senior Data Engineer to drive the evolution of our data delivery platform while leading a team of data engineers. • This is a player-coach role: you will architect our next-generation data stack, build proofs-of-concept (POCs), and prove out new technologies before we commit to them at scale — and you will also manage and grow a team of engineers who report directly to you. • You will partner closely with engineering leadership to shape the technical direction of our pipelines while staying hands-on in the systems yourself • We are deliberately moving away from a locked-in, vendor-heavy stack toward a flexible, largely open-source architecture that keeps our options open. • We also expect our engineers to work in a modern, AI-assisted way — using AI coding tools and prompt-based workflows to move faster without compromising quality. • You should be energized by evaluating tools, building POCs, and making pragmatic, evidence-based decisions about what we adopt next. • This is a build-and-prove role — you are expected to write code, design schemas, profile queries, and get into the details to understand the "how" and "why" behind every pipeline, while also mentoring your team to do the same.

Role Description We are looking for a highly technical, hands-on Senior Data Engineer to drive the evolution of our data delivery platform while leading a team of data engineers. This is a player-coach role: - Architect our next-generation data stack. - Build proofs-of-concept (POCs) and prove out new technologies before committing to them at scale. - Manage and grow a team of engineers who report directly to you. - Partner closely with engineering leadership to shape the technical direction of our pipelines while staying hands-on in the systems. We are deliberately moving away from a locked-in, vendor-heavy stack toward a flexible, largely open-source architecture that keeps our options open. We expect our engineers to work in a modern, AI-assisted way: - Use AI coding tools and prompt-based workflows to move faster without compromising quality. - Evaluate tools, build POCs, and make pragmatic, evidence-based decisions about what we adopt next. This is a build-and-prove role: - Write code, design schemas, profile queries, and understand the "how" and "why" behind every pipeline. - Mentor your team to do the same. - Team Leadership & People Management: Lead, manage, and grow a distributed team of data engineers (across North America and India). - AI-Assisted Development: Champion the use of AI coding assistants and prompt-based development. - Hands-On POCs & Prototyping: Build proofs-of-concept to validate new tools and patterns. - Tech Stack Strategy & Architecture: Help shape the technical vision for our ETL and data platform. - Platform Modernization: Drive the migration away from Azure Databricks toward a more open, flexible stack. - Build & Own Pipelines: Design, build, and optimize robust ETL pipelines. - Deep System Integration: Master all systems upstream and downstream to ensure seamless data delivery. - Operational Excellence: Establish testing frameworks, QA plans, observability, and CI/CD practices. - Technical Leadership Through Influence: Set technical standards and raise the bar across a distributed team. - Domain Mastery: Rapidly learn the nuances of the Advertising and Market Research domain. Qualifications - 8+ years in data engineering / ETL, with a strong track record as a hands-on engineer. - Hands-on experience using AI coding tools and strong prompt-based development skills. - Expert-level SQL and RDBMS skills with deep experience in SQL Server and Postgres. - Hands-on experience with technologies such as ClickHouse, dbt, and open-source data pipeline tools. - Strong, hands-on AWS experience. - Demonstrated ability to independently prototype, benchmark, and evaluate new technologies. - Strong proficiency in Python (or similar) for building and automating data pipelines. - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Requirements - Previous experience in Advertising, Media, or Market Research (Bonus Points). - Familiarity with containerization (Docker, Kubernetes) and infrastructure-as-code (Bonus Points). - Experience with streaming/real-time data technologies (e.g., Kafka) (Bonus Points). Benefits - Medical, Dental & Vision Insurance - 401k with Company Match - Flexible PTO - Commuter Benefits - Gym Discounts - Summer Fridays

As the Vice President, Client Partnership – Brands & Agencies, you will serve as a senior commercial leader responsible for one of MediaRadar's most strategically important client segments. Leading a team of approximately 15 Client Partners and senior individual contributors, you will own the full client relationship lifecycle across our brand and agency accounts—driving retention, deepening product adoption, and identifying new opportunities for revenue expansion. You will set the strategic direction for how we engage with brands and agencies at scale, serving as both a player and coach who brings deep industry knowledge, executive presence, and a relentless focus on client value. As a key member of MediaRadar's commercial leadership team, you will shape cross-functional strategy, contribute to company culture, and ensure that client-centricity is embedded in everything we do.

Role Description As the Vice President, Client Partnership – Brands & Agencies, you will serve as a senior commercial leader responsible for one of MediaRadar's most strategically important client segments. Leading a team of approximately 15 Client Partners and senior individual contributors, you will own the full client relationship lifecycle across our brand and agency accounts—driving retention, deepening product adoption, and identifying new opportunities for revenue expansion. You will set the strategic direction for how we engage with brands and agencies at scale, serving as both a player and coach who brings deep industry knowledge, executive presence, and a relentless focus on client value. As a key member of MediaRadar's commercial leadership team, you will shape cross-functional strategy, contribute to company culture, and ensure that client-centricity is embedded in everything we do. Qualifications - 10+ years of experience in client-facing roles within the media, advertising, or adtech ecosystem, with demonstrated expertise managing brand and/or agency relationships at a senior level. - At least 5 years of people management experience, including leading managers and senior individual contributors across a team of 10 or more. - Proven track record of owning and growing a large book of business, with measurable results across client retention, revenue expansion, and strategic account development. - Deep familiarity with how brands and agencies plan, buy, and measure advertising—including knowledge of media planning processes, agency holding structures, and advertiser decision-making dynamics. - Experience in a data-driven B2B environment, ideally within SaaS, adtech, media intelligence, or marketing technology. - Strong executive presence with a demonstrated ability to build and sustain C-suite and VP-level client relationships. - Ability to influence cross-functional teams and drive strategic alignment across Sales, Product, Marketing, and Operations. - Operational rigor, with experience implementing account planning frameworks, forecasting disciplines, and team performance systems. - Passion for coaching and developing talent, with a track record of building high-performing, values-driven teams. - Bachelor's degree required; MBA or relevant advanced degree is a plus. Requirements - Lead, mentor, and develop a team of ~15 Client Partners and senior ICs, each managing a portfolio of brand and agency accounts. - Define and execute client relationship strategies tailored to the brands and agencies segment. - Leverage your firsthand knowledge of brand marketing and agency operations to drive credibility and relevance with clients. - Build and sustain executive-level relationships with top brand and agency clients. - Collaborate closely with Sales, Customer Success, Product, and Marketing to align on account strategy. - Establish and continuously improve best practices for account planning, QBRs, success metrics, and renewal and upsell motions. - Partner with Finance and RevOps on forecasting, performance tracking, and strategic planning across client accounts. - Contribute to MediaRadar's broader commercial culture by fostering collaboration, integrity, and a growth mindset. Benefits - Medical, Dental & Vision Insurance - 401k with Company Match - Flexible PTO - Commuter Benefits - Gym Discounts - Summer Fridays

• Design and execute risk-based audit and sampling programs across classification, reference data, and governed datasets. • Test outputs against authored rules, definitions, and quality thresholds, documenting pass/fail evidence. • Quantify quality across dimensions (accuracy, completeness, consistency, timeliness) and track trends over time. • Validate the effectiveness of human-in-the-loop review, identifying where validation is or is not catching errors. • Investigate root causes of quality issues and recommend rule, process, or training improvements. • Produce clear audit findings, scorecards, and assurance reporting for governance and leadership. • Maintain audit trails and evidence sufficient to support internal and external scrutiny. • Partner with Governance to refine rules and thresholds based on observed failure patterns.

• Translate authored data rules and quality thresholds into automated, executable quality checks. • Build and maintain data quality monitoring, alerting, and dashboards across governed datasets. • Integrate quality checks into data pipelines, classification workflows, and governance tooling. • Automate detection of rule conflicts, duplicates, and reference data anomalies at scale. • Develop tooling that supports auditors, analysts, and stewards in their day-to-day work. • Instrument human-in-the-loop workflows to capture validation outcomes and quality signals. • Maintain reliable, performant data quality infrastructure and supporting data flows. • Partner with Governance to make rules executable and to close gaps between definition and enforcement.

• Partner with Data Operations and Governance to identify high-value opportunities for AI and automation across data delivery and data quality workflows. • Build small, self-contained, plug-and-play solutions — prompts, low-code workflows, scripts, and lightweight agents — that deliver incremental efficiency without standing up large models or heavy systems. • Translate governance rules, definitions, and taxonomies into prompt and automation logic that produces accurate, consistent output. • Prototype rapidly, measure operational impact, and iterate solutions based on real results and validator feedback. • Deploy solutions into production data operations and support adoption, monitoring, and handoff. • Recognize when a need exceeds what a contained solution can deliver, and serve as the conduit to larger-scale deployment by helping define clear, actionable requirements for engineering and platform teams. • Maintain prompt libraries, automation assets, and documentation with clear versioning. • Track solution performance against scale, efficiency, accuracy, and consistency targets and report on the gains realized. • Stay current on AI and automation techniques and responsible-AI practices, and share them across teams.