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Mid-market SaaS, popular data role in metro with broad skill requirements increases applicant density.
Core data engineering skills are transferable, though banking/regulated experience is preferred for better fit.
Explicit 10+ years requirement plus specific cloud, PySpark, and Terraform skills enforce strict candidate filters.
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Design, build, and maintain scalable data engineering components handling approx. 1TB data in personal banking.
Translate business requirements into production-ready data solutions with minimal oversight and full ownership of development lifecycle.
Ensure deployed systems meet uptime, scalability, and performance standards while collaborating with cross-functional teams.
10+ years of software development experience.
5+ years hands-on experience with cloud-based data engineering, specifically with GCP or similar cloud ecosystems.
Technical expertise in Python, PySpark, Dataproc, Cloud Functions, Airflow Composer, NoSQL databases (BigQuery, Firestore), advanced SQL, and Terraform.
Experience with data warehousing, database design, CI/CD pipelines, and GIT version control workflows.
Experienced in building and managing large-scale, high-performance data applications in financial services or regulated industries.
Proficient in data platform architectures including data warehouse and lakehouse, with a focus on security and scalability.
Able to independently own end-to-end solution design and delivery within an AI-powered, cloud-native digital banking environment.