Data Engineer: Remote Pipelines & Analytics for Investments

Willow Advanced Partners; Baltimore (MD); On-site; USD 110,000 - 141,000; Full time

Benefits offered by this job

Health insurance

401(k) or pension plan

Tuition reimbursement

Flexible work environment (remote work

Career growth opportunities

Job summary

Willow Advanced Partners, a leading alternative investment firm, is seeking a Data Engineer to join our team in Baltimore, MD. This role focuses on designing, building, and maintaining scalable data pipelines to support our investment strategies and decision-making processes.

You will collaborate with cross-functional teams to understand data needs, develop robust data models, and ensure data quality and performance.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3-5 years of experience in data engineering.
• Strong data modeling, ETL, and database management expertise.
• Strong Python and SQL programming; familiarity with Hadoop or Spark.
• Experience with AWS or Azure is a plus.

Responsibilities

• Design, build, and maintain efficient, scalable data pipelines to support our investment strategies.
• Collaborate with cross-functional teams to understand data requirements and deliver actionable insights.
• Develop and implement data models and algorithms to enhance our investment decision-making processes.
• Ensure data quality and integrity through robust data validation and testing procedures.
• Optimize data storage and retrieval processes to improve overall system performance.

Skills

Python

SQL

Hadoop

Spark

Big Data

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

PostgreSQL

Azure

Job description

Willow Advanced Partners, a leading alternative investment firm, is seeking a Data Engineer to join our team in Baltimore, MD. This role focuses on designing, building, and maintaining scalable data pipelines to support our investment strategies and decision-making processes.

You will collaborate with cross-functional teams to understand data needs, develop robust data models, and ensure data quality and performance.