Data Warehouse Architect

RESPONSIBILITIES AND DUTIES  

Data Architecture & Platform Strategy 

• Lead the architecture, design, and evolution of Avid’s enterprise data warehouse and data platform capabilities, with a focus on scalable, trusted, and business-ready data products. 

• Define and promote modern data modeling patterns, including dimensional modeling, star schemas, semantic layers, curated marts, and governed source-of-truth datasets. 

• Translate business needs into practical data architecture, platform patterns, technical requirements, and solution designs that can be implemented by data engineering teams. 

• Partner with leadership and stakeholders to shape the data platform roadmap, balancing near-term delivery needs with long-term architecture, maintainability, and data trust. 

Technical Leadership & Engineering Oversight 

• Serve as a hands-on technical leader for complex data warehouse, data engineering, and analytics enablement initiatives. 

• Review and guide technical design, data models, SQL logic, transformation patterns, data quality checks, and pipeline approaches to ensure durable and scalable solutions. 

• Lead technical problem solving across data discrepancies, source-system gaps, integration issues, and reporting inconsistencies. 

• Establish engineering standards, reusable design patterns, documentation expectations, and development practices for the Data Platform team. 

Team Leadership & Delivery Management 

• Provide day-to-day direction, coaching, and delivery oversight for data warehouse engineers, data engineers, and platform support resources. 

• Help manage intake, prioritization, Jira discipline, sprint planning, backlog grooming, status reporting, and delivery commitments across Data Platform workstreams. 

• Support resource planning, work allocation, and escalation management to ensure critical business and executive reporting needs are delivered with quality and predictability. 

• Act as a leadership bridge between the Director, Data Platforms and the day-to-day execution of the engineering team. 

Data Quality, Governance & Trusted Reporting 

• Champion data quality, consistency, and reliability across enterprise datasets used for financial, operational, sales, product, and executive decision-making. 

• Partner with Data Owners, Finance, Revenue Operations, Sales Operations, and Analytics teams to align datasets to governed definitions and approved sources of truth. 

• Drive root-cause analysis and remediation plans for data anomalies, reconciliation gaps, reporting conflicts, and source-system inconsistencies. 

• Support development of data quality scorecards, control checks, exception logs, lineage documentation, and trust indicators for critical enterprise data assets. 

Collaboration & Stakeholder Enablement 

• Partner with business and technical stakeholders to understand data needs, clarify requirements, explain tradeoffs, and align delivery to business outcomes. 

• Collaborate with BI and analytics teams to ensure curated datasets effectively support tools such as Power BI, Excel, and other reporting or analytics platforms. 

• Communicate data platform plans, risks, dependencies, and delivery status clearly to both technical and non-technical audiences. 

• Mentor team members and promote a culture of ownership, technical excellence, accountability, and continuous improvement. 

QUALIFICATIONS & SKILLS  

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Data Analytics, Business, Finance, or a related field. 

• 10+ years of experience in data warehousing, data engineering, analytics engineering, enterprise reporting, business intelligence, or related data platform roles. 

• 3+ years of experience providing technical leadership, team leadership, delivery oversight, solution architecture, or architecture guidance across data platform initiatives. 

• Strong experience designing and implementing enterprise data warehouse solutions, dimensional models, star schemas, curated marts, and source-of-truth datasets. 

• Strong understanding of business and financial metrics used in operational reporting and executive decision-making, including ARR, bookings, billings, pipeline, revenue, retention, and customer/product analytics. 

• Experience partnering with business stakeholders, data owners, analytics teams, finance teams, revenue operations, product teams, and engineering teams. 

• Demonstrated ability to lead complex data initiatives from requirements and design through delivery, validation, documentation, and adoption. 

TECHNICAL REQUIREMENTS 

• Advanced SQL skills, including complex joins, window functions, CTEs, data validation logic, reconciliation logic, and performance-aware query design. 

• Hands-on experience with Snowflake or similar modern cloud data warehouse platforms. 

• Strong understanding of ELT/ETL design patterns, data pipeline orchestration, data transformation frameworks, and production support practices. 

• Experience designing data models that support BI tools such as Power BI, Tableau, Domo, Excel, or similar analytics platforms. 

• Working knowledge of Python or another scripting language for data analysis, automation, validation, or troubleshooting. 

• Experience with Jira, Agile delivery practices, backlog management, documentation, and cross-functional delivery tracking. 

• Strong understanding of data quality controls, metadata, lineage, data governance, access controls, and documentation standards. 

PREFERRED SKILLS, EXPERIENCE & CAPABILITIES 

• Experience supporting SaaS, subscription, finance, revenue operations, sales operations, or customer analytics data environments. 

• Experience working with Salesforce, CPQ, billing systems, subscription systems, finance systems, RevOps platforms, or related systems of record. 

• Experience leading teams that include onshore and offshore engineers, contractors, data analysts, data owners, or platform support resources. 

• Experience modernizing legacy reporting environments and moving organizations toward governed, scalable, self-service data products. 

• Experience building or guiding data quality frameworks, control tables, exception management processes, reconciliation workflows, and executive confidence scorecards. 

• Experience supporting high-visibility executive reporting, board reporting, revenue reporting, or other business-critical data products. 

• Familiarity with data cataloging tools, metadata management, semantic layer design, and enterprise data governance frameworks. 

BEHAVIORAL TRAITS & CORE COMPETENCIES 

• Strong ownership mindset with the ability to operate as both a hands-on technical leader and a trusted partner to business stakeholders. 

• Excellent communication skills, with the ability to explain complex data architecture, platform, and data quality topics to non-technical audiences. 

• Strong leadership presence with the ability to coach team members, drive accountability, and create clarity in ambiguous or fast-moving situations. 

• Practical problem solver who balances speed, quality, architecture discipline, and business impact. 

• Strong attention to detail and a high bar for data quality, documentation, maintainability, and stakeholder trust. 

Salary Ranges:

MIN 145,050.00 to MAX 217,576.00 USD

The salary range shown reflects the company's good faith full target range for this position at the time of posting. The company may update or modify this range at any time and endeavors to keep this posting current. Compensation decisions are based on factors including geographic location, experience, skills, education, and business needs. While the full range is posted for transparency, offers are typically made within the lower to middle portion of the range.

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