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Mid-level, popular data engineer role in a metro with broad skill requirements increases competition.
Core data engineering skills transfer across industries, though hedge-fund domain knowledge increases specificity.
Explicit 5–8 years plus required Python/SQL and reporting skills raise shortlisting strictness.
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Design and build scalable data pipelines integrating multiple data sources, including databases and APIs.
Develop, maintain, and optimize interactive reports and dashboards, preferably using Power BI, ensuring data accuracy and timeliness.
Write and manage Python scripts for data processing, automation, and support business reporting needs.
5–8 years of professional experience in data engineering or related roles.
Proficiency in Python programming for data manipulation and automation.
Strong experience with databases (SQL) and data retrieval from APIs.
Power BI experience strongly preferred; exposure to Snowflake and financial services domain advantageous but not mandatory.
Experienced in building end-to-end reporting solutions with strong data visualization skills, especially using Power BI.
Comfortable optimizing data pipelines and queries for performance and reliability in a financial services or hedge fund environment.
Able to translate business stakeholder requirements into technical data engineering and reporting solutions with attention to data accuracy and detail.