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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, popular data engineer title, metro market, and broad skill requirements increase competition.
Low — core data engineering skills are highly transferable across industries despite marketing analytics preference.
Explicit 8+ years requirement plus mandatory Spark, ETL, Airflow, and cloud experience drives strict screening.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and maintain scalable, resilient data pipelines using cloud-native technologies for digital acquisition marketing.
Optimize batch and streaming data processing frameworks to support real-time and batch analytics across platforms.
Own data quality, platform performance, troubleshooting, and mentor junior engineers while contributing to architecture and CI/CD automation.
Minimum Requirements
Bachelor's degree in Computer Science, Engineering, Information Systems, or related technical field.
8+ years of experience in Data Engineering or Software Engineering.
Strong programming skills in Java and/or Python; hands-on experience with Apache Spark and ETL/ELT pipelines on cloud platforms.
Experience with SQL, relational and distributed databases, Apache Airflow or similar orchestration tools, version control with Git, and CI/CD practices.
Ideal Candidate Profile
Experienced with cloud platforms (preferably AWS) and big data tools like Databricks, Delta Lake, Kafka, Docker, and Kubernetes.
Demonstrates strong ability to translate business requirements into optimized data engineering solutions within Agile/Scrum environments.
Proven track record of delivering production-ready, high-quality data engineering features and mentoring junior team members.