Applicantz is a global leader in 3D design, engineering, and entertainment software, known for fostering a progressive culture and creativity. The Analytics Engineer will design, build, and maintain scalable data pipelines and models that power marketing analytics and reporting, ensuring marketing teams have reliable data for strategic decisions.
Responsibilities:
- Develop and maintain a unified marketing data warehouse (e.g., Snowflake, BigQuery) to ensure reliability, performance, and accessibility
- Define and implement best practices for data ingestion, transformation, and governance
- Align KPIs and metrics to marketing and business objectives for consistent reporting across tools and dashboards
- Integrate data from MarTech platforms (e.g., Marketo, Salesforce, Adobe) into centralized data systems
- Work with engineering to build automated pipelines using tools like Fivetran, dbt, and Git for version control and deployment
- Ensure data consistency and completeness across marketing systems and analytics platforms
- Collaborate with marketing, sales, and finance teams to deliver actionable insights through dashboards and reports
- Support advanced analytics use cases such as attribution modeling, campaign performance analysis, and customer segmentation
- Implement continuous improvement practices for marketing data processes and reporting
- Establish and enforce data quality standards (accuracy, timeliness, consistency)
- Maintain documentation for data definitions, taxonomies, and standardized KPIs across analytics tools
Requirements:
- SQL
- Building/maintaining data warehouse experience
- Data modeling
- Strong SQL/Snowflake is a must
- Proficiency in cloud data warehouses (Snowflake, BigQuery)
- Familiarity with marketing analytics tools (Marketo, Salesforce, Google Analytics, Power BI)
- Knowledge of version control (Git)
- Understanding of marketing metrics (ROI, CLV, attribution, funnel analysis)
- Power BI experience nice to have
- Scripting/coding is nice to have
- GitHub is nice to have
- Claude proficiency is nice to have
- Experience in marketing analytics or supporting marketing operations
- Ability to translate complex data concepts into actionable insights for non-technical stakeholders
- Familiarity with predictive and prescriptive analytics techniques for marketing optimization