Senior Data Engineer

Job Description

Responsibilities

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• Design, build, and maintain scalable data pipelines and data workflows across a modern data environment.
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• Develop and optimize data solutions using Snowflake, dbt, and Airflow .
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• Build and enhance data lakes and data platforms , integrating data from a variety of internal and external sources.
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• Develop reliable ETL/ELT processes to support reporting, analytics, and downstream applications.
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• Establish data transformation and modeling frameworks using dbt .
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• Develop and manage workflow orchestration using Apache Airflow .
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• Optimize Snowflake environments for performance, scalability, reliability, and cost.
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• Partner with data analysts, technology teams, and business stakeholders to understand requirements and translate them into effective data solutions.
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• Implement data quality, monitoring, testing, and governance practices across pipelines and data products.
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• Troubleshoot data pipeline and platform issues and proactively identify opportunities for improvement.
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• Contribute to the ongoing evolution of the firm's data architecture and engineering standards.
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• Clearly communicate technical solutions, project status, risks, and recommendations to both technical and non-technical audiences.
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Qualifications

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• 5+ years of experience in data engineering, data platform engineering, or a related discipline .
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• Strong hands-on experience with Snowflake .
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• Experience building and maintaining data pipelines using modern ETL/ELT technologies.
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• Strong experience with dbt and data transformation/modeling.
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• Experience with Apache Airflow or similar workflow orchestration platforms.
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• Experience designing and building data lakes, data warehouses, and/or modern cloud data platforms .
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• Strong SQL skills and experience working with large, complex datasets.
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• Experience with Python or another programming language commonly used in data engineering.
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• Understanding of data architecture, data modeling, data quality, and data governance principles.
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• Ability to work effectively in a fast-paced, collaborative environment.
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Preferred Qualifications

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• Experience working within financial services, private equity, investment management, banking, hedge funds, or asset management .
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• Experience working with financial or investment-related datasets.
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• Exposure to cloud platforms such as AWS, Azure, or GCP .
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• Experience with additional modern data technologies and cloud-based data platforms.
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• Experience supporting data initiatives involving analytics, AI, or machine learning.
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