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Broad mid-level data engineering role in metro with common experience band increases applicant competition.
Core data engineering skills transferable, though media/marketing domain experience is preferred.
Explicit 4–6 years and mandatory cloud, warehouse, orchestration, and MLOps skills make filtering strict.
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Own the data architecture including designing a harmonized data mart reconciling media spend, impressions, offers, trade investment, and sell-out on a common weekly grain.
Define and maintain the variable dictionary for the data systems.
Manage MLOps responsibilities including deployment, automation of data refresh, CI/CD, model monitoring, and cost optimization.
4 to 6 years of relevant experience in data engineering or related fields.
Proficiency in data modelling and warehouse design.
Strong SQL (advanced), Python, and experience with cloud data platforms like Snowflake, BigQuery, or Databricks.
Experience with orchestration tools (Airflow/dbt), MLOps, source-system integration, CI/CD, and understanding of data governance and cost optimization.
Experienced data engineer with hands-on ownership of data architecture and harmonization across multiple data sources.
Skilled in end-to-end MLOps and automation within cloud data platforms.
Capable of integrating source systems and implementing CI/CD pipelines for continuous deployment and monitoring of data models.