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Key skills for this role
· Build and maintain data ingestion pipelines from APIs and other data sources
· Write efficient Python and SQL for data transformation and processing
· Support ETL/ELT workflows, microservices and ensure timely data availability
· Troubleshoot pipeline failures and assist in performance improvements
Marketing Data Support
· Assist in ingestion and modeling of data from Meta Ads and similar platforms
· Help create datasets for:
o Campaign performance reporting
o Lead funnel tracking
· Develop familiarity with:
o Campaign structure (campaign/ad set/ad level)
o Basic performance metrics (CTR, CPC, CPA)
o Conversion tracking concepts
Business Collaboration
· Work with marketing and analytics teams to understand data requirements
· Support analysis related to lead quality and campaign performance
· Help translate business needs into data queries and datasets
Data Quality & Maintenance
· Implement basic data validation checks
· Monitor pipelines and resolve data issues
· Maintain documentation for pipelines and datasets
· Required Skills & Qualifications
· Core Technical Skills
· Proficiency in Python (data processing, API handling)
· Strong SQL skills
· Experience with data ingestion from APIs (basic handling of pagination, retries)
· Familiarity with workflow orchestration tools (e.g., Airflow or similar)
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Chennai, IND
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, USA
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, USA
· Exposure to cloud data warehouses (BigQuery, etc.)
Ad Platform Exposure
· Basic understanding of Meta Ads platform concepts
· Familiarity with:
· Marketing metrics (CTR, CPC, conversions)
· Lead generation and funnel basics
· Willingness to learn deeper AdTech concepts
Soft Skills
· Good problem-solving and debugging skills
· Ability to work in a collaborative, cross-functional environment
· Clear communication of technical work and issues
Good to Have
· Exposure to other marketing platforms (Google Ads, etc.)
· Experience with tools like dbt or similar transformation frameworks
· Understanding of event tracking (GA4, etc.)
What Success Looks Like
· Reliable execution of data pipelines with minimal supervision
· Accurate and timely delivery of marketing datasets
· Growing understanding of marketing data and business use cases
· Effective collaboration with senior engineers and stakeholders
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