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Analytics Engineer (short-term)
JOB SUMMARY
Roles
Job details
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 ManagementMaintain 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 StandardsAdvanced 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 DocumentationOmni 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
RequiredExpert 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). PreferredAnalytics 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 HaveFamiliarity with system design concepts and Java-based applications. Experience managing data flow from VM-hosted environments or transactional databases (MySQL).
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 ManagementMaintain 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 StandardsAdvanced 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 DocumentationOmni 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
RequiredExpert 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). PreferredAnalytics 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 HaveFamiliarity with system design concepts and Java-based applications. Experience managing data flow from VM-hosted environments or transactional databases (MySQL).
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Globaldev Group Ukraine
