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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain large-scale, automated data ingestion pipelines on Databricks for programmatic advertising data from various DSPs, SSPs, and third-party partners.
Own end-to-end ingestion processes including partner onboarding, pipeline productionisation, monitoring, cost optimization, and incident management.
Enhance and expand MiQ’s Unified Ingestion Service and ETL framework to accelerate onboarding and data integration across the organization.
Minimum Requirements
2–3 years of hands-on experience in data engineering and data integration with cloud platforms (AWS preferred; Azure or GCP acceptable).
Proficiency in PySpark notebook development (preferably on Databricks) and advanced SQL for building high-throughput data pipelines.
Experience with data ingestion methods including APIs, S3, SFTP/FTP, email drops, event streams, and CDC.
Work Experience Required: 2–3 years relevant experience in data engineering and integration
Ideal Candidate Profile
Experienced data engineer comfortable managing complex, large-scale data ingestion in cloud environments using modern lakehouse technologies (Delta Lake, Delta Live Tables, Unity Catalog).
Candidate who excels in collaborating across multi-disciplinary teams including trading, analytics, product, and external partners to deliver business-critical data solutions.
Operates with strong ownership of pipeline lifecycle from onboarding through incident resolution, emphasizing data quality, reliability, and cost-effectiveness.