The RoleAs a
Data Engineer at theGuarantors, you will play a vital role in the development, deployment and maintenance of our data infrastructure. You will work within our data engineering team to build, optimize, and maintain data pipelines, ensuring the availability and reliability of data for analytical and business purposes. You will help to execute on processes that leverage intelligence capabilities through advanced analysis of data sets, and that bring data and insights closer to the end user. This is an excellent opportunity for someone who is enthusiastic about data and eager to learn and grow in the field of data engineering.
LocationThis will be a hybrid role based in NYC.
What You'll Do- Data Ingestion and ETL/ELT: Assist in designing and implementing data pipelines to collect, ingest, and transform data from various sources into a structured format.
- Data Quality: Collaborate with the team to monitor and maintain data quality standards, perform data validation, and resolve data quality issues.
- Data Warehousing: Assist in the design and maintenance of data warehousing solutions to store and manage large volumes of data efficiently.
- Automation and Orchestration: Work on automating routine data engineering tasks to improve efficiency and reliability.
- Data Apps: Develop and maintain lightweight data applications for ML interfaces, simple CRUD operations, and quick interactive analysis.
- Performance Optimization: Identify and implement optimizations to all parts of the data stack to improve data pipeline performance and reduce processing times.
- Documentation: Create and maintain documentation for data pipelines, processes, and data flows.
- Collaboration: Collaborate with cross-functional teams including data analysts, data scientists, and business stakeholders to understand data requirements and deliver data solutions.
- Continuous Learning: Stay up to date with industry best practices and emerging technologies in data engineering.
- Modeling Support: Curate and maintain data sets and pipelines that are crucial to core operational data models, to our feature store and to other AI/ML workflows.
What You'll Bring- Bachelor's degree in Computer Science, Information Technology, or a related field.
- Demonstrated application of SQL and Python scripting skills.
- Basic understanding of data modeling concepts.
- Proficiency in using data integration and ETL tools (e.g., Stitch/Talend, Airbyte, Fivetran, etc).
- Knowledge of data warehousing concepts and technologies (e.g., Snowflake, AWS Redshift, Google BigQuery, etc).
- Experience with AI-integrated development (tools such as Cursor, Claude Code, Github Copilot or similar).
- Excellent problem-solving skills and attention to detail.
- Strong communication and teamwork skills.
- Ability to work in a fast-paced, collaborative environment.
- Eagerness to learn and adapt to new technologies and tools.
Nice To Have- Master's degree in Computer Science, Information Technology, or a related field.
- 1+ years of experience working for a small- to medium-sized technology company as a data engineer or similar role.
- Experience with cloud computing platforms such as AWS, Azure, or Google Cloud.
- Knowledge of data orchestration and workflow management tools (e.g., Dagster, Airflow).
- Familiarity with data governance and security best practices.
- Previous internship or coursework related to data engineering.
Benefits- Opportunities to make an impact within a fast growing company
- Medical, dental, & vision insurance, beginning day one
- Health savings account with employer contribution
- Flexible spending accounts (healthcare, dependent care, commuter)
- 401(k)
- Generous PTO and paid holidays
- In-office lunch perk
- Flexible working hours
- Paid parental leave
- Company sponsored short and long term disability
Base SalaryThe base salary range is between $115,000 - $130,000 annually.
Base salary does not include other forms of compensation or benefits. Final offer amounts are determined by multiple factors, including prior experience, expertise, location and current market data and may vary from the range above.
