As an Analytics Engineer, you will be responsible for designing, developing, and maintaining data infrastructure and analytics solutions to support data-driven decision-making and reporting. You will collaborate with other internal teams such as Business Intelligence, Credit/Structuring, Operations, Legal, and other stakeholders to understand business requirements and translate them into technical solutions. You will also engage with external counterparties on data-related matters. Your role will potentially involve working with large and complex data sets, implementing data pipelines, and ensuring data accuracy, integrity, and availability.

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 and external clientele to understand their requirements and develop analytics solutions that meet their needs. This may include building dashboards, reports, and interactive visualizations.

· Counterparty Management: Work with external counterparties in situations such as reconciliations, data issues, additional data requests, etc.

· 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.

Qualifications:

· Bachelor's degree in Computer Science, Information Systems, Data Science/Analytics, or a related field.

· 3 years of experience as an Analytical Engineer, Data Engineer, Data Analyst,

· 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.

· Deep understanding of data engineering principles and tools, including data modeling, ETL/ELT practices, data transformation with dbt, data warehousing in Snowflake, and cloud computing with AWS.

· Intermediate experience with Python scripting.

· Proficiency in Tableau Desktop and Tableau Cloud is advantageous.

· Strong analytical and problem-solving skills, with the ability to transform complex data into actionable insights.