Senior Associate Data Engineer

Responsibilities:

• Develop and maintain data infrastructure: Design, build, and optimize data pipelines, ETL/ELT processes, and data warehouses to support efficient data collection, storage, and retrieval.
  
• Data modeling and schema design: Define data models and schemas to enable efficient data analysis, reporting, and visualization. Ensure adherence to data governance and data quality standards.
  
• Data transformation and manipulation: Cleanse, transform, and aggregate data to derive meaningful insights. Identify data inconsistencies, outliers, and anomalies and implement appropriate solutions.
  
• Implement data analytics solutions: Collaborate with different company departments to understand their requirements and develop analytics solutions that meet their needs.
  
• Documentation and communication: Document data processes, data flows, and data structures. Clearly communicate technical concepts and findings to non-technical stakeholders such as Credit/Structuring, Operations, Legal, etc.
  

Requirements

Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Data Science/Analytics, or a related field.
  
• 4+ years of experience as an Data Engineer, Analytical Engineer, Data Analyst, Business Intelligence Engineer, or similar role
  
• Experience working with finance-related data sets (ex: FinTech, Lending, Financial Services, or related industries)
  
• Advanced SQL skills and experience working with complex data sets.
  
• Understanding of the following is advantageous:
  o Data Modeling
  o Data Governance
  o ETL/ELT practices
  o Data transformations with dbt
  o Data warehousing with Snowflake
  o Cloud computing with AWS
  o Data orchestration tools (e.g. Airflow, Dagster)
  o API Usage and Integration
  
• Strong analytical and problem-solving skills, with the ability to transform complex data into actionable insights.
  
• Excellent communication and collaboration skills, with the ability to interact effectively with both technical and non-technical stakeholders.
  
• Strong attention to detail and a commitment to delivering high-quality work within deadlines.
  
• Willingness to stay updated with emerging technologies, tools, and best practices in data engineering and analytics. Ability to adapt to evolving business needs and work in a fast-paced environment.