We are seeking a highly skilled Analytics Engineer to provide immediate coverage and stabilization for our media data infrastructure. As our primary data architect during this transition, you will be responsible for maintaining a complex Google BigQuery environment, ensuring data integrity from diverse sources (Supermetrics, APIs, and manual vendor files), and migrating our transformation logic into a scalable, transparent framework to support our move into Omni Analytics.
Working hours: Ideally 8-5pm EST. But we may have some flexibility, depending on the developer’s availability.
Key Responsibilities
1. Pipeline & Ingestion Management
- Maintain & Troubleshoot: Monitor existing data ingestions, including Supermetrics, custom APIs, and Python-based scripts.
- Vendor Data Handling: Manage ingestion of varied vendor formats (CSV/ZIP) into BigQuery, handling dynamic schema changes and sharded raw tables efficiently.
- Environment Monitoring: Oversee pipelines interacting with VM environments and transactional databases (e.g., MySQL) to ensure reporting continuity.
2. Transformation, Modeling & Standards
- Advanced Modeling: Maintain and optimize existing SQL/Python scripts while formalizing transformations into production-ready tables using dbt.
- Performance Optimization: Implement incremental loading strategies, partitioning, and clustering within BigQuery to manage costs and query speed.
- Classification & Normalization: Apply and update complex logic to categorize media spend and performance. This includes normalizing varied vendor naming conventions into internal CP/Mavenn standards (Campaigns, Placements, Creatives, and UTM structures).
3. BI Strategy & Documentation
- Omni Integration: Collaborate with the Analyst team to ensure BigQuery "Production" tables are optimized for the Omni Analytics modeling layer.
- Knowledge Transfer: Finalize and expand upon technical documentation to ensure no loss of institutional knowledge during the transition.
Technical Qualifications
Required
- Expert BigQuery (SQL): Master-level SQL (window functions, UDFs, script optimization) and GCP environment management.
- Marketing Tech Stack: Deep experience with advertising data schemas (Meta, Google, TikTok, etc.) and ingestion tools like Supermetrics or Fivetran.
- Problem Solving: Proven ability to "reverse engineer" legacy scripts to extract and document business logic.
- Version Control: Proficiency with Git-based workflows (GitHub/Bitbucket).
Preferred
- Analytics Engineering: Hands-on experience with dbt (data build tool).
- Programming: Proficiency in Python for data ingestion, API interaction, and transformation.
- Agency Experience: Experience managing multi-client, multi-schema environments.
- BI Expertise: Familiarity with the Omni Analytics platform or similar modeling-first BI tools.
Nice to Have
- Familiarity with system design concepts and Java-based applications.
- Experience managing data flow from VM-hosted environments or transactional databases (MySQL).
