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Tier-1 brand plus remote and metro location increase applicant density despite senior specialization.
Deep data engineering expertise and private markets context make backgrounds less transferable.
Senior VP technical leadership plus mandated Snowflake, Python, cloud, dbt and team management implies strict filtering.
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Lead hands-on architecture and development of scalable, reliable data pipelines and analytics platforms, focusing on Snowflake, SQL, and Python.
Provide technical leadership and accountability for data engineering outcomes across the Private Markets Data Engineering team, including managing a team of Data Engineers.
Collaborate with business stakeholders to translate strategic objectives into technical initiatives, prioritize technical solutions, and promote data governance best practices.
Proven senior technical experience with deep hands-on expertise in Snowflake, SQL, and Python.
Demonstrated leadership in senior technical roles, including managing or providing technical direction to engineers.
Strong understanding of data architecture, pipeline design (preferably dbt), pipeline tooling (e.g., Dagster, Airflow), and cloud platforms (Azure or AWS).
Work Experience Required: Not explicitly mentioned in the JD
Experienced in balancing long-term technical strategy with fast-paced delivery in dynamic environments.
Skilled in engaging and influencing stakeholders at multiple levels to align technical solutions with business goals.
Experienced in managing technical teams and driving adoption of advanced analytics, AI/ML, and automation in data engineering contexts.