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Popular data-engineer title and metro location increase competition; seniority and niche cloud skills moderately reduce it.
Core data engineering skills are transferable, but banking domain and regulatory experience increase specificity.
Explicit 10–13 years requirement and mandatory cloud, PySpark, BigQuery, and Terraform make filters strict.
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Design, build, and maintain scalable data engineering components handling ~1TB of personal banking data on cloud platforms.
Translate business requirements into production-ready, high-performance, reliable data solutions with minimal oversight.
Take full ownership of the development lifecycle, ensuring uptime, scalability, and alignment with standards and best practices.
10+ years of software development experience with 5+ years in cloud-based data engineering.
Expertise with Python, PySpark, Dataproc, Cloud Functions, Airflow Composer, and advanced SQL including query optimization.
Experience with NoSQL databases like BigQuery and Firestore, Google Cloud Platform, Terraform, and CI/CD pipelines.
Work Experience Required: 10+ years in software development, including 5+ years cloud data engineering experience; Location: Hyderabad, India.
Experienced in designing and optimizing data warehousing, lakehouse architectures, and large-scale data platforms within regulated domains such as financial services or banking.
Proficient collaborator who can manage end-to-end solution design and deployment in cloud ecosystems using infrastructure as code (Terraform) and version control (GIT).
Comfortable working in hybrid environments emphasizing security, scalability, and seamless user experience in fintech or digital banking SaaS contexts.