OneMagnify

Role Description This role owns the integrity and clarity of OneMagnify’s financial data. As an Accounting Manager, you’ll lead core accounting operations, guide a small team, and ensure our reporting supports confident, timely decision-making across the business. You’ll balance hands-on execution with leadership, shaping how we close, report, and continuously improve. Your work directly influences how we scale, invest, and operate. The Impact You'll Have: - Ensure that financial reporting is accurate, timely, and actionable. - Provide leadership with a clear view into performance, enabling smarter business decisions. - Create the foundation for financial discipline and operational confidence. - Connect closely with teams across finance, operations, and leadership. - Translate accounting data into insights and improve process efficiency. What You'll Do: - Own the close and reporting cycle. - Lead month-end and year-end close processes with a focus on accuracy, consistency, and timeliness. - Prepare and review journal entries across assets, liabilities, revenue, and expenses. - Ensure financial statements reflect a complete and accurate view of the business. - Lead and develop the accounting team. - Mentor and support accounting staff, setting clear expectations and raising the bar on quality. - Create structure and accountability within the team while encouraging growth and ownership. - Serve as a go-to resource for complex accounting questions and decisions. - Maintain integrity across the general ledger, reconciliations, and subsidiary ledgers. - Identify and resolve discrepancies proactively. - Ensure compliance with accounting principles, internal policies, and audit requirements. - Collaborate with finance leadership and operations teams to align reporting with business needs. - Support external auditors and tax partners by delivering clean, well-organized documentation. - Identify opportunities to streamline workflows and reduce manual effort. - Implement improvements that make reporting faster, clearer, and more reliable. - Help evolve accounting practices to support a tech-enabled, growing organization. Qualifications - Bachelor’s degree in Accounting, Finance, or related field. - 5+ years of experience in accounting, including leadership or supervisory responsibility. - Strong knowledge of accounting principles and financial reporting practices. - CPA strongly preferred. - Experience with enterprise accounting systems (Workday experience a plus). - Advanced proficiency in Microsoft Excel. - Strong analytical thinking and attention to detail. - Ability to lead work and collaborate effectively across teams. Future-Ready Skills (Nice to Have) - Experience improving accounting workflows through automation or AI-enabled tools. - Familiarity with integrated financial and operational reporting in digital or services organizations. - Exposure to ERP optimization or system implementations. - Experience supporting private equity-backed or high-growth environments. - Comfort working with data visualization or reporting tools alongside finance systems. Benefits - Medical, dental, and vision coverage. - 401(k) retirement plan. - Paid holidays. - Flexible Time Off (FTO) for recharging. - Programs focused on wellness, financial security, and professional growth. Company Description We are an equal opportunity employer. We believe that innovative ideas and solutions start with unique perspectives. That's why we're committed to providing every employee a workplace that's free of discrimination and intolerance. We're proud to be an equal opportunity employer and actively search for like-minded people to join our team. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job functions, and to receive benefits and privileges of employment. Please contact us to request accommodation.

• Own and evolve the integrated delivery operating model • Set the decision rights, accountability frameworks, and quality bar • Lead the Central Delivery Organization • Set the direction and performance bar for OneMagnify's central delivery organization • Own Delivery Economics and Commercial Intelligence • Ensure Client Value Is Delivered • Set the AI-Enabled Delivery Direction • Own Global Delivery Operating Model and Scale Levers • Partner Across the Business and with Clients • Uphold Quality, Risk, and Value Integrity

• Lead the optimization of cross-cloud Salesforce implementations (Data Cloud, Experience Cloud, Marketing Cloud, Sales Cloud, Service Cloud, custom platforms) to improve Consumer Marketing performance, scalability, and maintainability. • Evaluate existing architectures to identify technical debt, performance bottlenecks, and opportunities for consolidation or modernization. • Design extensible, future‑ready solutions that support enterprise growth, high data volumes, and complex business processes. • Architect and optimize integrations between Salesforce and enterprise data platforms (data lakes, data warehouses, MDM systems, ERP, and external services). • Optimize system performance through refined data models, indexing strategies, asynchronous processing, and optimized automation. • Design for high availability, fault tolerance, and secure access across enterprise environments. • Partner with business leaders, product owners, and delivery teams to translate business needs into optimized technical solutions. • Provide architectural guidance and decision frameworks that balance speed, cost, risk, and long‑term value. • Influence enterprise standards, best practices, and architectural roadmaps. • Ensure solutions adhere to enterprise security, compliance, and regulatory requirements. • Implement role‑based access controls, data protection strategies, and audit‑ready architectures within Salesforce and connected systems. • Drive continuous optimization through monitoring, analytics, and performance tuning. • Evaluate and adopt emerging Salesforce features and data technologies to improve solution efficiency and reduce total cost of ownership. • Collaborate with delivery teams on scalable design patterns and optimization best practices.

• Collaborate with strategic clients to identify where AI and data can drive meaningful action — not just generate insights • Translate client business challenges into technical approaches that are both rigorous and achievable • Serve as a trusted advisor who can simplify complex AI concepts for non-technical stakeholders • Provide hands-on technical direction for generative AI projects, including architecture decisions and solution design • Apply expertise in LLMs, data science, and object-oriented programming to guide delivery from prototype to production • Leverage tools like Databricks, Python, R, and SQL across the project lifecycle — including building and managing data pipelines, feature engineering, and model deployment within the Databricks ecosystem • Lead and develop a cross-functional team of data scientists, AI engineers, and software engineers • Set clear expectations, support career growth, and build a team culture oriented around craft and client outcomes • Model the technical and communication standards you expect from the team • Drive alignment across AI, analytics, strategy, and engineering disciplines within OneMagnify • Partner with delivery and operations teams to ensure AI workstreams integrate cleanly into broader project execution • Represent the AI practice in client-facing settings alongside strategy and creative counterparts • Stay current on the evolving AI landscape — new models, platforms, tools, and use cases — and bring relevant developments into client conversations and internal delivery • Contribute to OneMagnify's point of view on AI-enabled solutions and how the practice continues to grow

• Serve as a primary point of contact for Dealers, Independent Repair Facilities, and customers via phone and email • Provide clear guidance on program rules, eligibility, and technical website issues tied to active automotive programs • Maintain consistent follow-through on inquiries so issues are resolved, not just acknowledged • Conduct semi-scripted outbound mystery shop calls to dealers and independent repair facilities • Observe and assess customer service interactions against program guidelines • Capture findings accurately to support quality and program improvement efforts • Work across multiple systems simultaneously, including client-owned platforms and OneMagnify tools • Use Salesforce Service Cloud to manage contact records, cases, and follow-ups • Apply solution-focused thinking to identify root causes and escalate issues appropriately • Facilitate dealer and customer rewards programs, including processing financial payouts as defined by client programs • Ensure data accuracy and compliance when handling sensitive personally identifiable information (SPII) • Partner with operations and delivery teams to keep programs running smoothly end to end • Communicate regularly with OneMagnify teammates through Microsoft Teams, email, phone, and on-camera meetings • Share patterns, issues, and feedback that help improve program execution and customer experience • Operate within OneMagnify’s quality standards and documented work practices

• Define and execute Emodo's global publisher development strategy across web, app, and CTV • Build, manage, and develop a high-performing publisher development team across regions • Set coverage models, quota frameworks, and performance standards for the function • Represent publisher development at the executive level, including board-facing reporting on supply growth • Personally lead pursuit and closure of strategic publisher relationships at the enterprise tier • Build C-level and VP-level relationships at premium publishers, networks, and aggregators • Negotiate complex, multi-market agreements including rates, payment terms, and platform integration requirements • Drive contract execution from term sheet through legal sign-off with speed and precision • Partner with Publisher Operations to design onboarding processes that compress time-to-revenue for new partners • Hold accountability for publisher revenue contribution, not just signed agreements • Serve as senior escalation point for business-critical issues across the publisher portfolio • Work directly with Product and Engineering to translate supply-side market needs into platform priorities • Collaborate with the Demand and Ad Operations teams to align supply quality with advertiser outcomes • Contribute to go-to-market strategy, pricing, and packaging decisions as a member of the senior leadership team • Track and synthesize supply-side trends, competitive dynamics, and publisher market shifts • Bring structured intelligence into executive and board-level conversations with actionable implications • Represent Emodo at industry events, publisher summits, and trade conferences

• Leverage data tools and capabilities to deliver superior service to client's customers and to advance the Data & Analytics Road Map • Conduct discovery and end-to-end data analysis to understand customer needs and to help develop plans and activities to improve data quality • Elicit, analyze, interpret business and data requirements to develop complete data product solutions, includes review data models (entity relationship diagrams, dimensional data models), ETL and business rules, data management, governance, lineage, metadata and reporting elements • Manipulate large data sets using SQL to understand patterns in the data • Perform data profiling using various tools to learn the shape of the data to help inform data quality checks and/or curation rules that need to be developed • Support customers in interpreting data and remediating issues when required • Engage with data owners, stewards to implement, maintain, enhance data governance, quality, security and privacy requirements, and related policies and standards • Prepare technical specifications for data ingestion and transformation rules • Partner with data architects to build data models for efficient consumption of data • Support the development of standards and best practices within the Data Analysis team, this includes documentation templates and agile development methodologies

• Lead Data Platform Architecture and Delivery • Own the technical direction and delivery of cloud-native data platforms built on Databricks and AWS • Lead the design and implementation of Lakehouse architecture — Delta Lake, Unity Catalog, Spark-based processing — across client engagements • Ensure scalability, performance, security, and cost optimization are built into solutions from the start, not addressed after delivery • Build and Optimize Data Pipelines • Oversee ingestion, transformation, and orchestration pipelines across both batch and streaming workloads • Apply AWS-native services (Glue, Step Functions, Lambda, Redshift, S3) alongside Databricks to build reliable, production-grade pipelines • Establish reusable pipeline patterns and delivery accelerators that raise consistency across the team • Enable AI, ML, and GenAI Use Cases • Ensure data is accessible, trusted, and production-ready to support model development and deployment across AI and GenAI initiatives • Collaborate closely with data science and analytics teams to align platform capabilities with active and planned AI programs • Contribute to client AI roadmap conversations by translating platform decisions into clear enablement strategies • Engage Clients on Technical Strategy • Participate in client-facing architecture reviews and technical strategy sessions, communicating complex platform concepts as practical business outcomes • Support senior leadership in executive briefings and help clients make confident decisions about platform direction and investment • Partner with strategy and delivery teams to scope and structure data platform engagements • Develop the Data Platform Team • Lead, mentor, and grow a team of data engineers, architects, and platform specialists • Set technical standards and create an environment where craft and continuous improvement are expected • Identify skill gaps and help build the team's capabilities alongside the growth of OneMagnify's data practice

OneMagnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter customer experiences and delivering highly integrated solutions across digital, media, and technology. By combining deep industry expertise with advanced analytics and artificial intelligence, we enable our clients to make better decisions, move faster, and compete more effectively in dynamic markets. Role Summary As a Data Engineer at OneMagnify, you'll build and maintain the data pipelines and integrations that power enterprise analytics and client-facing solutions. This is a craft-focused role where the quality of your work has a direct line to the insights clients rely on — and to the AI and analytics products built on top of that data. You'll work alongside data scientists, analysts, and architects to make sure data moves reliably, cleanly, and at scale. The Impact You'll Have Good data engineering is invisible when it works and painfully obvious when it doesn't. In this role, you're the reason it works. The pipelines you build connect source systems — ERPs, CRMs, data warehouses — to the analytics and AI layers where client decisions get made. When that infrastructure is solid, the models are more accurate, the reporting is trustworthy, and the business cases hold up. You'll work on engagements with large B2B clients in sectors like automotive, industrial, and enterprise technology — organizations managing complex, high-volume data environments where reliability and data quality aren't optional. Your work directly affects how well those clients can act on their data, whether that's optimizing a supply chain, personalizing a customer experience, or tracking campaign performance across channels. You'll collaborate closely with data scientists, analysts, and data architects — not just handing off pipelines, but actively contributing to how data domains are structured and how quality standards get defined and upheld across the platform. What You'll Do Build and Maintain Data Pipelines - Develop integrations between data sources and target systems including ERPs, CRMs, and data warehouses using Databricks and AWS-native services (Glue, Step Functions, Lambda) - Configure, customize, and deploy data engineering applications that support multiple data domains reliably and at scale - Leverage the Databricks Lakehouse platform — Delta Lake, Unity Catalog, and Spark-based processing — to optimize pipeline performance and maintainability Establish and Uphold Data Quality - Develop and enforce data cleansing and standardization guidelines that keep data consistent and trustworthy across systems - Use strong SQL skills to validate, troubleshoot, and resolve data issues before they surface downstream - Partner with data architects to set quality standards that the broader team can operate against Connect Systems Through Integration - Build integrations using APIs and modern pipeline approaches to connect systems that weren't designed to work together - Align pipeline design with enterprise data flows in close collaboration with data scientists and analysts - Ensure integrations are built for durability, not just initial delivery Support Data Platform Users - Work directly with business users and data stewards to diagnose and resolve data issues within the platform - Translate technical pipeline behavior into clear explanations for non-engineering stakeholders - Contribute to documentation and processes that make the data platform easier to use and maintain over time What You'll Need - Bachelor's degree in Computer Science, Information Systems, or a related field — or equivalent professional experience - 5+ years of hands-on experience in data engineering development or implementation - Strong SQL skills across data analysis, validation, and troubleshooting - Hands-on experience with Databricks (Delta Lake, Unity Catalog, Spark) and AWS data services (Glue, Redshift, S3, Lambda, or Step Functions) - Familiarity with APIs and integration methods for connecting systems across an enterprise Future-Ready Skills (Nice to Have) - Experience with Databricks MLflow or Feature Store supporting AI/ML pipeline workflows - Familiarity with marketing data ecosystems: CRM platforms, CDP architectures, or Martech/Adtech data flows - Exposure to data observability or governance tooling (lineage tracking, data cataloging, pipeline monitoring) - Experience in a digital agency, marketing services, or consulting environment with multiple concurrent client data environments - Working knowledge of streaming data pipelines or event-driven architectures (e.g., Kafka, Kinesis) Benefits We believe great work happens when people have the support and flexibility they need to thrive. Our benefits include medical, dental, and vision coverage, a 401(k) retirement plan, paid holidays, and Flexible Time Off (FTO) so you can take time away to recharge when you need it. We also offer additional programs focused on wellness, financial security, and professional growth. We are an equal opportunity employer We believe that Innovative ideas and solutions start with unique perspectives. That’s why we’re committed to providing every employee a workplace that’s free of discrimination and intolerance. We’re proud to be an equal opportunity employer and actively search for like-minded people to join our team. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job functions, and to receive benefits and privileges of employment. Please contact us to request accommodation.

• Build and Deploy Analytical Models • Design, develop, and validate predictive models — forecasting, classification, regression, and segmentation — with rigorous diagnostics and clear documentation • Conduct A/B testing and causal analyses to support experimentation programs and measure the impact of client initiatives • Develop optimization solutions (linear, mixed-integer, multi-objective) and ensure models are production-ready with monitoring in place • Use Databricks for large-scale data processing and machine learning workflows, integrating data from diverse sources across complex client environments • Monitor and validate data flows, develop data quality reporting, and perform root-cause analysis when issues surface • Collaborate with data engineering teams on MLOps practices — MLflow pipelines, model deployment, lifecycle management, and version control via Git/GitLab • Execute advanced analyses, synthesize findings, and build executive-ready presentations and visualizations using Tableau and Power BI • Develop new metrics and KPI reports that give clients and internal stakeholders a clearer view of business performance • Communicate effectively with both business and technical audiences — adapting your framing to the room • Work with business partners and data engineering teams to elicit requirements, define business rules, and translate client needs into technical specifications • Contribute to project meetings to align on scope, timelines, and analytical approach across multi-member engagements • Test database changes prior to release and ensure data designs align with defined standards and governance requirements • Apply data governance, privacy, and compliance standards consistently across analytical work • Document models, processes, and business rules clearly enough that others can reproduce, validate, and build on your work