Senior Manager, Analytics Engineering

Key Skills

Amazon Elastic Compute Cloud-EC2, Amazon RedShift, Amazon Simple Storage Service (S3), Apache Airflow, AWS, Big Data Technology, Data Biuld Tool - dbt, Postgres, PowerBI, Python Programming, SAS, SQL, Tableau, Unix Operating system

Job Description

Collaborate with business partners and stakeholders to understand their analytical needs, and translate the business needs into analytical data product design and implementation. Design the credit risk and credit facility data products to help the company with the current and future strategy. Lead a team of data analytics engineers to develop the analytical data pipelines and reports using tools like SQL, DBT, Python, Unix, Airflow, Redshift, AWS. Lead a team of data analytics engineers to develop production data systems that generate financial reports and loan tape files for credit facility. Design and develop data governance, data quality measurement and data remediation processes and monitoring frameworks. Drive and define data modeling and coding best practices and standards and provide technical leadership for the data analytics engineering team. Conduct code review of data pipelines and analytical code. Seek and surface root causes of credit risk and financial reporting data issues and address them at the source. Conduct research in data gaps, recommend and implement solutions for business process improvements. Clearly articulate and present complex data analysis concepts and issues to diverse audiences in technical and non-technical terms.

Position based at headquarters and may be assigned to unanticipated worksites throughout the U.S. as determined by management. Telecommuting permitted. 

Minimum Requirements: Master’s degree or foreign degree equivalent in Operations Research, Business Analytics, Engineering, Information Technology Management, Mathematics, or related field, plus five (5) years of experience in job offered, in data analysis, or related occupation.

Special Requirements: Position requires each of the following skills:

1. Programming in SAS, Python;
2. Using SQL to conduct data analysis;
3. Developing analytical reporting in BI tools such as QuickSight, Tableau, or PowerBI;
4. Delivering cross functional action plans by communicating complex analytical insights and compelling risk mitigating solutions;
5. Production transformation analytical data pipeline system design and maintenance;
6. Managing data products in Big Data analytical database warehouses such as Redshift, Snowflake, etc.;
7. Developing production transformation data pipelines using Python, SQL, Airflow, AWS;
8. AWS Cloud data engineering tools such as EC2, S3, Postgres; and
9. Setting up the data quality monitoring for key financial business metrics.

Manages others: YES: Four (4) Analytical Engineers

Travel: NO (per mgr: Domestic: 1 day per quarter. International: 3-4 days every six months)

What we offer

• Make a positive impact on the lives of our customers via financial inclusion
• International exposure & work experience
• Professional development opportunities 
• Promote from within
• Competitive salaries with strong Stock Option package
• Health, dental and vision insurance
• Paid time off
• Flexible schedule including remote work
• 401(k)
• Health Savings Account
• FSA
• Commuter Benefits
• Short and Long Term Disability
• Life Insurance
• Employee Assistance Program
• Open office design 
• Onsite gym
• Casual dress code
• Company outings