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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 employer, generalist Data Engineer title, metro location, and broad technical requirements increase competition.
GCP and data-engineering skills transfer across industries, though telecom integrations slightly raise domain specificity.
Multiple mandatory GCP, Python, Kafka, and Airflow technical requirements tighten candidate filtering.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable ETL and ELT data pipelines using Google Cloud Platform services (BigQuery, Cloud Storage, Cloud Composer, Dataflow, Pub/Sub, Cloud Functions).
Optimize data pipelines for performance, reliability, and cost efficiency, including managing data models, storage, and processing costs.
Collaborate with data scientists, analysts, business stakeholders, internal teams, and external partners to translate data requirements into effective technical solutions and ensure timely project delivery.
Minimum Requirements
Strong practical experience with Python for data processing and scripting.
Hands-on expertise in Google Cloud Platform, especially BigQuery, Cloud Storage, Cloud Functions, Cloud Composer, and Pub/Sub.
Experience designing, developing, and maintaining ETL/ELT data pipelines and proficiency in SQL.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in building and optimizing cloud-native data architectures and pipelines using GCP data services.
Skilled in automating workflows and managing real-time streaming data, including Kafka integration with Python.
Able to translate complex business requirements into scalable, high-quality data engineering solutions within collaborative, cross-functional teams.