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Tier-1 brand, metro location, mid-level (5+) popular data engineering role and broad skills drive high competition.
Strong core data engineering skills transfer across industries, though financial domain experience is beneficial.
Explicit 5+ years requirement plus mandatory Snowflake, Python, SQL and enterprise data engineering standards increase shortlisting strictness.
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Lead design, development, and optimization of scalable data pipelines and platforms for structured/unstructured data in portfolio management.
Own end-to-end data engineering solutions including ingestion, transformation, storage, and serving layers supporting analytics and AI.
Provide technical leadership, mentor engineers, and drive best practices for reliable, scalable, and maintainable data initiatives.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
5+ years of relevant data engineering experience.
Strong expertise in Python, SQL, cloud data platforms (e.g., Snowflake), and modern data pipeline/orchestration frameworks.
Experience designing data models, ETL/ELT processes, data quality frameworks, and working knowledge of Git, CI/CD, and software engineering standards.
Experienced in architecting and delivering enterprise-scale data engineering solutions with a focus on scalability, reliability, and performance.
Skilled at leading technical decisions and mentoring teams across complex data initiatives in cross-functional environments.
Familiar with integration of data platforms with analytics/AI applications and implementing observability, monitoring, and cost-optimization strategies on cloud platforms.