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Mid-level generalist data engineer role with common skillset at a recognizable firm increases applicant competition.
Marketing/web-analytics emphasis moderately limits transferability, but core data engineering skills remain broadly applicable.
Explicit 4-6 years requirement plus mandatory cloud, BigQuery, SQL, Python, and integration skills enforces strict filters.
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Design and implement scalable data engineering pipelines in Google Cloud Platform focused on web analytics.
Integrate diverse data sources including AWS Aurora, SAP, and Salesforce ensuring smooth data flow and accessibility.
Manage at least 1-2 end-to-end data engineering projects from concept to deployment, demonstrating project management and technical expertise.
4-6 years of experience as a Data Engineer with a focus on web analytics data pipelines.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related STEM field.
Hands-on experience with GCP and AWS data services like Pubsub, Dataflow, Bigquery, Cloud Functions, Glue, Redshift, S3.
Advanced proficiency in SQL, Python, Bash scripting and experience integrating data from diverse sources via APIs.
Experienced in executing complete data engineering projects showing strong project management.
Comfortable working across cloud platforms (GCP and AWS) with marketing and enterprise system datasets.
Able to collaborate with cross-functional teams to design and optimize data solutions for decision-making.