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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 employer, metro location, and popular data-engineering title raise applicant density despite seniority and niche tech needs.
Core data engineering skills are transferable, but retail domain experience and leadership expectations require closer fit.
Multiple mandatory senior, technical, and leadership requirements increase filtering stringency.
Job Description
Structured overview of role & requirementsAbout This Role
Lead design and architecture of scalable, resilient data platforms on Google Cloud using Big Data technologies like Apache Spark and Hadoop.
Drive end-to-end development and optimization of data pipelines with Scala, Spark, and GCP services including BigQuery, Dataflow, and Pub/Sub.
Manage and mentor a team of data engineers, oversee production stability, and collaborate with stakeholders on strategy, architecture, and modernization initiatives.
Minimum Requirements
12+ years of experience in Data Engineering or related domains.
Hands-on expertise in Scala, Apache Spark, Hadoop ecosystem, and Google Cloud Platform services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Composer).
Experience leading and managing engineering teams, including at least 1 year supervisory experience.
Education: Bachelor's in Computer Science with 5 years software engineering or Master's with 3 years software engineering plus 4 years in data engineering/analytics or equivalent combination.
Ideal Candidate Profile
Proven ability to architect and deliver large-scale, high-performance data platforms in a cloud environment (especially GCP).
Experienced in strategic stakeholder engagement and translating business priorities into technical roadmaps.
Strong leadership skills focused on team growth, high-quality delivery, and fostering technical excellence.