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Strong employer brand, metro Hyderabad location, and common Engineering Manager title increase candidate density.
Core data engineering skills are transferable, though financial document-processing domain knowledge limits direct fit.
Explicit 8–12 years, managerial experience and specific data engineering tech stack required.
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Lead and manage a team of 5–8 engineers focused on building scalable, automated data engineering platforms for financial data and document processing.
Own architecture, design, and development of cloud-native, event-driven data pipelines leveraging AWS and modern automation/AI techniques.
Collaborate with product, architecture, and engineering leadership to translate complex business problems into scalable engineering solutions and drive execution excellence.
8-12 years of software engineering experience with strong data engineering expertise.
Prior experience leading engineering teams in a product-oriented environment.
Bachelor's degree in Engineering, Computer Science, or equivalent.
Strong experience with Python, Pandas, NumPy, PyArrow, FastAPI, PostgreSQL, DynamoDB, Redis, Elasticsearch, Amazon S3, Docker, and AWS cloud-native development.
Experienced in designing and operating large-scale, high-volume data processing pipelines and backend systems with strong architectural skills.
Comfortable leading technical and execution planning, coaching engineers, and driving cross-team alignment in a complex, product-driven organization.
Demonstrates a strong ownership mindset with emphasis on automation, system performance optimization, and simplifying complex engineering challenges.