Senior Software Engineer, Data Platform Job at Parafin (San Francisco)

Senior Software Engineer, Data Platform

Parafin

Location:
United States , San Francisco

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

230000.00 - 265000.00 USD / Year

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Job Description:

We’re looking for a seasoned software engineer to join Parafin’s Infrastructure team and lead the development of our next-generation Data Platform. This role is critical to ensuring that our data infrastructure is reliable, scalable, and developer-friendly as we continue to power financial services for small businesses. As a Senior Software Engineer, you’ll be responsible for designing, building, and maintaining the systems that ingest, transform, and serve data across the company. You’ll partner closely with Data Science, Platform Engineering, and Product Engineering teams to support data-driven product development and decision-making.

Job Responsibility:

Design and build robust, highly scalable data pipelines and lakehouse infrastructure with PySpark, Databricks, and Airflow on AWS
Improve the data platform development experience for Engineering, Data Science, and Product by creating intuitive abstractions, self‑service tooling, and clear documentation
Own and maintain core data pipelines and models that power internal dashboards, ML models, and customer-facing products
Own the Data & ML platform infrastructure using Terraform, including end‑to‑end administration of Databricks workspaces: manage user access, monitor performance, optimize configurations (e.g., clusters, lakehouse settings), and ensure high availability of data pipelines
Lead projects to improve data quality, testing, observability, and cost efficiency across existing pipelines and backend systems (e.g., migrating Databricks SQL pipelines to dbt, scaling data ingestion, improving data-lineage tracking, and enhancing monitoring)
Act as the primary engineering partner for the Data Science team—embedded closely to gather requirements, design scalable solutions, and provide end-to-end support on all engineering aspects of their work
Work closely with backend engineers and data scientists to design performant data models and support new product development initiatives
Share best practices and mentor other engineers working on data-centric systems

Requirements:

4+ years of experience in software engineering with a strong background in data infrastructure, pipelines, and distributed systems
Advanced proficiency in Python and SQL
Hands-on Spark development experience
Expertise with modern cloud data stacks—AWS (S3, RDS), Databricks, and Airflow—and lakehouse architectures
Hands‑on experience with foundational data‑infrastructure technologies such as Hadoop, Hive, Kafka (or similar streaming platforms), Delta Lake/Iceberg, and distributed query engines like Trino/Presto
Familiarity with ingestion frameworks, developer‑experience tooling, and best practices for data versioning, lineage, partitioning, and clustering
Strong problem-solving skills and a proactive attitude toward ownership and platform health
Excellent communication and collaboration skills, especially in cross-functional settings

Nice to have:

Experience with AWS infrastructure using Terraform
Familiarity with observability tools (e.g., Datadog) and cost tracking in cloud environments
Experience with financial systems or building platforms in a fintech setting
Prior work on ML infrastructure: Feature stores (e.g., Tecton), ML model lifecycle (training, deployment, monitoring, retraining), real-time inference
Contributions to internal tooling or open-source projects in the data ecosystem

What we offer:

Equity grant
Medical, dental & vision insurance
Work from home flexibility
Unlimited PTO
Commuter benefits
Free lunches
Paid parental leave
401(k)
Employee assistance program

Additional Information:

Job Posted:
February 21, 2026

Employment Type:

Fulltime

Work Type:

Hybrid work

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