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Senior specialist role at a known financial firm in a metro yields moderate applicant competition.
Core data engineering skills transfer across industries, though finance/asset-management experience is preferred.
Explicit 8–11 years plus mandatory Databricks, Spark, AWS, data architecture, and leadership raise filter strictness.
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Lead the design and delivery of scalable cloud data platforms, defining and governing cloud data architecture and engineering standards.
Design and develop scalable ETL/ELT pipelines using Python, Spark, and Databricks on AWS, ensuring data quality, performance, security, and platform reliability.
Provide technical leadership and mentorship to engineering teams, driving cloud modernization, automation, and CI/CD best practices.
8–11 years of experience in Data Engineering, Data Architecture, or related roles.
Proven experience designing and implementing cloud-based data platforms using AWS, Databricks, Python, Spark, and SQL.
Strong skills in data modeling, data warehousing, Lakehouse architecture, and cloud data engineering.
Work Experience Required: 8–11 years
Experienced in leading solution design, architecture discussions, and technical delivery in complex enterprise environments.
Technical expertise in cloud data platforms within Financial Services or Asset Management domains preferred.
Capable of balancing hands-on engineering with architectural leadership and mentoring responsibilities.