Director, Data Analytics

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Director of Data Analytics based in US - Remote Setup

Avid Technology is looking for an experienced, strategic and hands-on Director of Data Analytics who will lead all aspects of data management, analysis, and strategic insights at Avid. Reporting to the Vice President of Digital Business Technology, the successful candidate will be responsible for developing a highly scalable, reliable, and trusted data platform that will serve as the single source of truth for the company. Additionally, the individual will be responsible for the design, implementation, and support for all systems integrations across enterprise systems.  The Director of Data Analytics will play a critical role in driving the company's growth by leveraging internal data assets and analytics capabilities to enhance operational efficiency and enable data driven decision support across all functional areas.

KEY RESPONSIBILITIES

• Lead Business Intelligence efforts leveraging Snowflake, Power BI, Domo, SQL to transform business operations and analytics.

• Collaborate closely with cross-functional teams, including marketing, sales, finance, operations, and technology, to identify business needs and develop data-driven solutions. Establish strong and lasting partnerships across all business lines.

• Set and implement a strategy and roadmap for the data platform, business intelligence and analytics with a focus on enhancing end-user experience through self-service solutions, AI based data quality, speed of delivery, and high-quality results.

• Manage and mentor Data Analytics and Visualization team members, including hiring, career development, and performance reviews.

• Lead the engineering, delivery and support of data pipelines in Snowflake.

• Develop and provide ongoing support and maintenance for Domo/Power BI reports and dashboards, including troubleshooting and resolving issues as they arise.

• Manage, optimize and modernize the data infrastructure and technology stack to support a highly efficient development lifecycle, including data storage, ETL processes, data modeling, data dictionary, taxonomy, and data visualization tools.

• Train and enable business users on how to leverage the data provided in our data warehouse, data lake, and data marts.

• Implement and enforce data governance policies leveraging strong partnerships across the business to ensure data integrity and security.

• Communicate complex technical concepts to non-technical stakeholders in a clear and concise manner.

• Bring an innovative mindset and stay sharp of industry trends, emerging technologies, and best practices in data management, analytics.  Empower a data-driven culture within the organization, promoting data literacy, encouraging data-driven thinking, and driving data-driven decision-making at all levels.

• Demonstrate a high degree of creativity and problem-solving skills.

QUALIFICATIONS

• Bachelor’s degree in data Analytics, Computer Science, Statistics, Mathematics, or equivalent work experience.

• 10+ years of experience in a data role (Data Analyst, Data Engineer, Analytics Engineer, BI Engineer).

• Exceptional business acumen and the ability to translate complex data insights into actionable recommendations for senior leadership.

• 8+ years of experience with Power BI or Domo including DAX and Power Query.

• 8+ years experience developing and managing efficient ETL processes with tools such as FiveTran and Airflow.

• 3+ years of hands-on experience to automate Data Vault modeling with dbt Cloud

• 8+ years of experience with SQL, Python or other query languages.

• 5+ years experience with cloud-based data solutions, Snowflake Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Snowflake and/or equivalent cloud data technologies and platforms.

• 3+ years experience leading taxonomy management with solutions such as Synaptica.

• Expertise bringing together structured and unstructured data from various sources with solutions such as Hex.

• Advanced SQL and Python skills for data manipulation and orchestration.

• Hands-on experience implementing data capabilities and technologies supporting data pipelines, data integration, data transformation, analytics, reporting and modeling (e.g. AI/ML).

• Experience implementing and maintaining semantic data models.

• In-depth knowledge of data governance, security practices, and compliance regula