Happy Money is looking for a Senior Data Engineer to build and optimize the backbone of our data platform. You will design and implement high-impact, cloud-native solutions that improve data reliability, reduce latency, and scale with the business, playing a key role in enabling data products, real-time analytics, and cross-functional decision-making.
What You'll Do
- Architect, design, implement, and operate end-to-end data engineering solutions using Agile methodology.
- Develop and manage robust data integrations with external vendors and organizations, including complex API integrations.
- Collaborate closely with Data Analysts, Data Scientists, DBAs, and cross-functional teams to understand requirements and deliver high-impact data solutions.
- Lead and take ownership of assigned technical projects in a fast-paced environment.
- Drive continuous improvement in the quality, security, efficiency, and scalability of data pipelines and infrastructure.
What We're Looking For
- Bachelor of Science degree in Computer Science or equivalent practical experience.
- 4+ years of dedicated experience building and maintaining complex ETL/ELT pipelines.
- 3+ years of Python development experience, specifically building production-grade data APIs using FastAPI or similar frameworks.
- Strong expertise in SQL, including advanced query optimization and performance tuning.
- Expert-level proficiency in dbt implementation, including managing models, macros, and incremental and dynamic tables.
- Extensive hands-on experience with Snowflake, including performance optimization, data recovery using Time Travel, and advanced data modeling techniques.
- Practical experience with key AWS data services such as Kinesis, Firehose, Redshift, Spectrum, Elastic MapReduce, and Lambda; and container orchestration services like ECS and EKS.
Nice to Have
- Proven experience designing and building near real-time data processing systems.
- Experience with data observability tools for proactive monitoring of data quality, lineage, and pipeline health.
- Familiarity with modern data orchestration platforms such as Argo or Airflow.
- Hands-on experience with the full software development lifecycle (SDLC), including strong CI/CD practices for data pipelines and proficiency with data testing frameworks.
- Demonstrated ability to identify and adopt new technologies that improve data quality and reliability.
- Deep understanding of the data lifecycle, emphasizing the importance of high-quality data in applications, machine learning, business analytics, and reporting.
- Proven track record of mentoring junior team members.
- Experience with data ingestion tools like Singer is a plus.
- Knowledge of analytics tools such as Tableau, Plotly, and Pandas.
- Experience in the financial services industry.
Technical Stack
- Languages & Frameworks: Python, FastAPI, SQL, dbt
- Platforms & Databases: Snowflake, AWS (Kinesis, Firehose, Redshift, Spectrum, Elastic MapReduce, Lambda, ECS, EKS)
- Tools: Argo, Airflow, Singer, Tableau, Plotly, Pandas
Team & Environment
You will be part of a growing data organization that includes analysts, data scientists, and ML engineers.
Benefits & Compensation
- Compensation Range: $135,500 - $200,000 + RSUs + benefits + equity.
- Medical, Dental, Vision - multiple packages available.
- Life/AD&D Insurance - basic coverage at 100% company paid.
- Supplemental Short-term and Long-term Disability.
- FSA: Medical and Dependant Care.
- 401K.
- Equity packages for each role.
- Time Off: Vacation, Sick and Parental Leave.
- EAP (Employee Assistance Program).
- Financial Literacy Mentoring Program.
- Pet Insurance.
- Home Office Stipend.
Work Mode
This role is fully remote and open to candidates located anywhere in the Contiguous United States.
Happy Money is an equal opportunity employer committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
