Analytics Engineer in FinTech Data Science team ensuring data accuracy and usability. Transforming raw data into reliable models for business monitoring and insights.
About the role
- Analytics Engineer building Retool's analytics and BI stack. Develop ETL, define metrics, and create dashboards to drive data-informed decisions.
Responsibilities
- Build and maintain scalable ETL pipelines
- Design our Analytics and Business Intelligence architecture, assessing and implementing new technologies where fitting
- Work with our engineering teams to ensure robust instrumentation across areas of the product
- Become a subject matter expert on Retool’s data sources — understand their context and limitations, and maintain data lineage documentation to promote transparency for end users
- Support data governance efforts, ensuring alignment with all data privacy standards and regulations
- Participate in code reviews, advising on and adhering to coding standards and best practices
- Partner with business teams to deploy robust reports and analyses, surfacing key insights that shape Retool’s future direction
- Develop dashboards and define metrics that drive key business decisions
- Take ownership of our data stack to ensure that teammates are able to access the data they need to make decisions and that technical teams are able to quickly implement events
- Develop data sets to streamline operations, inform strategic priorities, and generate product insights
- Help define our data team structure and operating rhythm for the future; collaborate with stakeholders across finance, marketing, engineering, product, operations, and support
Requirements
- Background in Analytics Engineering, Business Intelligence, Data Engineering, or Data Analytics
- Ideally 4+ years of experience managing and building large, complex data sets across a range of sources
- Strong SQL and data modeling skills; ability to apply a range of data modeling techniques and philosophies to solve real-world problems
- Experience implementing data quality frameworks with automated testing and monitoring that catch critical issues without excessive noise
- Commitment to creating data documentation systems that enable self-service analytics and reduce repetitive stakeholder questions
- Ability to optimize cloud database performance through query tuning, table design, and strategic storage configurations
- Excellent business acumen with the ability to translate stakeholder requirements into data models
- Hands-on experience with data orchestration and transformation tools like dbt, Dagster, or Airflow
- Experience developing in a cloud data warehouse system like Databricks or Snowflake
- Comfortable with common git workflows and at least one scripting or statistical programming language (ideally Python and/or R)
- Skilled at data visualization, with strong opinions on the right way to distill information to various audiences
- A solution-oriented growth mindset; self-starter who thrives in a dynamic environment
- A bias towards communication and collaboration with business and technical stakeholders
- Quantitative rigor and systems thinking
- Prior startup experience preferred but not required
- Deep dbt knowledge, including the ability to write complex but maintainable jinja to customize our dbt deployment
- Deep experience with Spark/Databricks SQL and Delta Lake
- Deep experience with the Databricks platform, including Unity Catalog management, Workflows, DLT, and MLflow
- Experience using UX techniques to design highly usable, effective data products
- Experience designing data models for complex, highly technical products — particularly developer tools
Benefits
- Additional compensation in the form(s) of equity, and/or commission/bonuses are dependent on the position offered.
- Retool provides a comprehensive benefit plan, including medical, dental, vision, and 401(k).
- Generous benefits to all employees.
- Hybrid work location.
- For more information, please visit the benefits and perks section of our careers page.
Job title
Job type
Experience level
Salary
Degree requirement
No Education Requirement
Tech skills
Location requirements
Analytics Engineer developing and maintaining data models to support strategic decisions in Hostinger. Revolutionizing data use to enhance business insights and accessibility.
Data Engineer at Regions Bank focusing on designing and maintaining data structures for analytics. Collaborating with technical teams to deliver data - driven business value and products.
Analytics Engineer shaping Statista's reporting platform for data - driven decision - making. Focusing on BI tools like Power BI and improving report usability and transparency.
Director of Data & Analytics leading data strategy for Reach Financial, enhancing decision - making through a data - driven culture. Guiding a team to innovate and implement scalable data solutions.
Data Scientist creating scalable insights from unstructured data at AI safety company. Collaborating with engineering and research teams in a hybrid Paris location.
Senior Analytics Engineer owning the analytics data platform for parenting technology startup. Requires deep SQL expertise and data pipeline experience in a hybrid role.
Senior Analytics Engineer at Higgsfield AI translating product and finance metrics into data models. Collaborating cross - functionally to ensure consistent, reliable data for decision - making.
Senior Data Analytics Developer for Krux, building data infrastructure for innovative SaaS solutions in mining industry. Collaborating with a self - motivated team to drive company growth.
Lead Risk Analytics Consultant at Wells Fargo focused on model governance and risk management strategies. Collaborate across teams to enhance system stability and mentor junior staff.