Data Warehouse Engineer

It's fun to work in a company where people truly BELIEVE in what they're doing! We're committed to bringing passion and customer focus to the business. ABOUT AVID Avid makes technology and collaborative tools so creators can entertain, inform, educate and enlighten the world. Our customers are the visionaries behind the most inspiring feature films, television programs, news broadcasts, televised sporting events, music recording and live concerts. At Team Avid, we are committed to building a global organization that promotes and celebrates diversity and inclusion—drives innovation in a fun and highly-collaborative culture. We pride ourselves on our core values: We are empowered, trusted, inclusive and passionate. To learn how Avid powers greater creators or for more information, visit www.avid.com JOB SUMMARY Come and join us at Avid as a Data Owner (Remote), where you will play a critical role in ensuring that enterprise data used across revenue operations, finance, product analytics, and executive reporting is accurate, well-defined, and trusted across the organization. In this role, you will serve as the business authority responsible for the definition, quality, and governance of key business datasets. You will partner closely with the Data Platform, Analytics, Finance, Revenue Operations, and Engineering teams to ensure data used for reporting, forecasting, and operational decision-making is consistent, documented, and aligned with business definitions. You will help establish and maintain clear ownership of core data domains, ensuring business metrics and datasets are governed, documented, and consistently used across analytics, reporting, and operational workflows. RESPONSIBILITIES AND DUTIES Data Ownership & Governance Act as the data product owner for assigned enterprise data domains, serving as the authoritative source for business definitions, dataset usage, and metric consistency. Define, maintain, and govern authoritative business definitions for key metrics such as bookings, billings, revenue, ARR, MRR, pipeline, and other core performance indicators. Establish and enforce data governance standards, including dataset ownership, stewardship practices, access policies, and certification processes. Serve as the final decision authority when conflicts arise across dashboards, reports, and operational systems regarding metric definitions or data interpretation. Data Quality, Trust & Source of Truth Champion data accuracy, consistency, and reliability to ensure the enterprise data warehouse serves as the single source of truth. Proactively research data anomalies, outliers, and inconsistencies, identify root causes, and partner with engineering and analytics teams to resolve data integrity issues. Monitor ongoing data hygiene, standardization, enrichment, and reconciliation across systems. Promote data trust across the organization by ensuring enterprise reporting aligns to governed datasets and approved definitions. Collaboration & Enablement Partner closely with Data Platform, Data Engineering, Analytics, Finance, Revenue Operations, Product, and Sales Operations teams to support evolving business needs. Ensure curated datasets and pipelines align with approved definitions and source‑of‑truth systems. Collaborate with BI and analytics teams to ensure datasets effectively support tools such as Power BI, Excel, and other analytics platforms. Guide business stakeholders on the correct interpretation, usage, and limitations of enterprise datasets. Documentation & Discoverability Ensure business datasets are well-documented, searchable, and discoverable, maintaining data dictionaries, metadata, and lineage documentation. Support and drive adoption of enterprise data governance frameworks, including documentation standards and dataset certification. Data Thought Leadership Act as a data thought leader, helping shape best practices for metric definition, governance, and analytics enablement. Influence enterprise data strategy by promoting consistent, well-governed, and trusted data across reporting and operational workflows. QUALIFICATIONS & SKILLS Bachelor’s degree in Business, Information Systems, Data Analytics, Finance, or a related field. 5+ years of experience working with enterprise data in analytics, business operations, revenue operations, finance analytics, or data governance roles. Strong understanding of business and financial metrics used in operational reporting and executive decision-making. Experience working with BI and analytics tools such as Power BI, Tableau, Domo, Excel, or similar platforms. Strong understanding of relational data structures, data models, and enterprise reporting environments. Experience collaborating with data engineering or platform teams responsible for building and maintaining data pipelines. Demonstrated experience defining business metrics, KPI frameworks, and reporting standards. TECHNICAL REQUIREMENTS Proficiency in SQL for data exploration, validation, anomaly detection, and root‑cause analysis. Working knowledge of Python for data analysis, research, and investigation of data quality issues. Strong passion for data research, continuous improvement, and resolving discrepancies to maintain high-quality data assets. PREFERRED SKILLS, EXPERIENCE & CAPABILITIES Experience working with modern cloud data platforms such as Snowflake or similar enterprise data warehouses. Experience supporting and governing datasets related to revenue operations, finance reporting, and sales analytics, including ARR, MRR, bookings, billings, and pipeline metrics. Experience implementing or operating within data governance frameworks, including ownership models, stewardship practices, and metadata management. Experience working with SaaS operational systems such as Salesforce, subscription billing platforms, or related systems of record. Experience supporting organizations transitioning to modern data platforms and self-service analytics environments. Familiarity with data cataloging tools, dataset documentation frameworks, and metadata management solutions. Proven ability to resolve data trust issues across environments where multiple systems or reports produce conflicting results. BEHAVIORAL TRAITS & CORE COMPETENCIES Strong business acumen with the ability to translate complex business concepts into clear, structured data definitions. Excellent collaboration skills across both technical and business stakeholders. Clear and confident communicator, capable of explaining metrics and data concepts to non‑technical audiences. Strong analytical mindset and problem‑solving skills when investigating complex data discrepancies. Ability to balance data governance rigor with agile, evolving business requirements. Strong ownership mindset, accountability, and attention to detail. Avid is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us !