Define and execute the Analytics Engineering strategy and roadmap, modernizing data models into a modular, scalable, and efficient framework that enhances analytical capabilities
Design, build, and maintain robust data transformation pipelines, owning the source, business, and reporting layers, leveraging dbt for transformation and Apache Airflow for orchestration
Implement and optimize CI/CD workflows using GitHub, improving analytics developer productivity, deployment automation, and data integrity through rigorous testing and version control.
Develop and maintain Core Data Models in Tableau, ensuring well-structured, high-quality datasets that empower self-serve analytics across GTM teams
Coach and upskill team members on analytics engineering best practices while enabling business analysts with well-structured data models and intuitive tools for self-serve analytics
Lead the implementation of AI solutions to enhance the analytics journey. An example is Conversational Analytics initiative to provide stakeholders with an omnichannel analytics experience, enabling insights through SQL, no-code interfaces, and conversational interactions
Requirements
5+ years of experience in a relevant data/analytics engineering role within dynamic, outcome-driven organizations
Hands-on experience with cloud data platforms such as Snowflake, BigQuery, or Redshift
Advanced skills in SQL and Python, with extensive experience in data transformations, data modeling, and analytics engineering best practices
Experience with orchestration tools like Apache Airflow, Prefect, or Dagster
Strong understanding of DataOps principles, including data observability, automated testing, and performance monitoring
Ability to create analytics workflows using GitHub and CI/CD, increasing developer productivity and data pipeline efficiency
Experienced in using business intelligence tools such as Tableau or Looker to communicate insights and enable self-serve analytics
Proven ability to translate complex business concepts and metrics into elegant and easy-to-use data models
Demonstrated ability to build effective partnerships across diverse teams and influence decision-making with data
Strong communication and stakeholder management skills that foster trust in data
Comfortable with ambiguity. Able to work independently and take full ownership of projects with minimal guidance
Driven by curiosity and creativity to overcome challenges
Best-in-class attention to detail and an unwavering commitment to accuracy