Staff Analytics Engineer

Salary

This position is Palo Alto-based and will require hybrid work from the office 2 days per week. The Palo Alto base salary range for this full-time position is $225,000 - $275,000 + equity + benefits. Our salary ranges are determined by role, level, and location.

This is a high impact role within the AI & Data team. You will work across teams, help drive data-driven decisions and own the automated reporting systems. You will develop solutions to complex business problems characterized by imperfect data. You will gather, transform, and present data to enable data-driven decision-making. You will help scale the analytics we are offering to both internal and external stakeholders. You will also help us strengthen our capabilities to build, maintain strategic data assets & platforms, generate insights for critical business functions and drive the culture of clean data at EarnIn!

What You'll Do

Interface with Finance, Engineering and Analytics to understand data needs and deliver high quality data products (25%)
- Get familiar with finance & analytics domain at EarnIn and identify opportunities for process automation
- Build data functional expertise and own data quality for allocated areas of ownership.
- Create quality controls on data feed to ensure high quality data delivered for end product
- Design, build and launch new data extraction, transformation and loading processes in production as and when required
- Implement data governance practices, including data security, privacy, and compliance measures
- Deep analysis to uncover areas of opportunity and present recommendations that will help shape the strategy and operations of business stakeholders
- Create project related documentation for requirements, design, processing methodologies and changes planned and other relevant areas
- Provide analytical support for financial needs such as annual audits, new product revenue reporting and external lender inquiries
Champion data quality and governance throughout EarnIn by maintaining and extending a clean data ecosystem for the company (25%)
- Gather business requirements from key stakeholders across the company to identify and model key clean data entities needed for critical business functions and needs
- Work with analytical engineering and data engineer teams to create curated datasets in batch and real-time via modern data processing solutions.
- Ensure the curated datasets fulfill the main elements of data products - well designed, richly described, strongly governed, high quality, operationally reliable (within SLAs) and compliant with data privacy regulations
Streamline data flows from source and produce high quality data and pipelines (20%)
- Develop and maintain data pipelines, ETL processes, and data integration workflows to ensure efficient and accurate data acquisition from various internal & external sources using SQL, Python, or other scripting languages
- Work with data infrastructure to triage infra issues and drive to resolution and serve as the key point to bridge between data infrastructure and end customers
- Design, build, and optimize data architecture & models to support business reporting and analytics needs. Understand evolving business requirements to optimize/update data pipelines in SQL
- Monitor and optimize the performance of data systems, troubleshoot issues, and propose solutions for data-related problems
Design, develop and maintain scaled, automated, user-friendly systems, reports, dashboards, etc. that will support our financial needs (20%)
- Build and deliver high quality visualization and reporting solutions to support Finance business needs
- Design and create customized reports for all new financial reconciliation needs catering to their specific needs
- Automate reporting for Finance using Python, Periscope, Tableau, Amplitude and other EarnIn in-house business intelligence tools and platforms
Be a data and functional expert at EarnIn (10%)
- Stay up to date with industry trends and emerging technologies in the field of business intelligence and data analytics.
- Be a data SME related to fintech domain
- Identify and recommend BI and data tools that can be used within the company for increased productivity and scalability

What We're Looking For

Bachelor/ Master degree in Engineering / Analytics related fields
6+ years of relevant work experience in Analytics, Business Intelligence, Data Science or relevant field
6+ years experience in custom ETL design, implementation and maintenance.
5+ years experience with schema design and dimensional data modeling
5+ years experience in writing complex SQL queries and Python
5+ years experience working with Snowflake / Databricks or similar distributed compute systems
5+ experience with business intelligence tools such as Tableau, Power BI, or QlikView.
5+ years of working with relational databases (Redshift, PostgreSQL) and big data structures
5+ years of experience in collaborating with cross-functional teams
Proficient in at least one major data processing framework like Spark
Hands on experience working in cloud environments: AWS, GCP, Azure
Experiences working with finance team is preferred not required
Ability to analyze data to identify deliverables, gaps and inconsistencies. Excellent problem-solving and analytical skills
Fintech industry experience preferred

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