Senior Software Engineer, Data Platform

Unchain Data; San Francisco (CA); Hybrid; USD 220,000 - 265,000; Full time

Benefits offered by this job

Medical, dental & vision insurance

Work from home flexibility

Unlimited PTO

Commuter benefits

Free lunches

Paid parental leave

401(k)

Employee assistance program

Job summary

Parafin is seeking a Senior Software Engineer to join the Infrastructure team and lead the Data Platform development. You will design, build, and maintain data ingestion, transformation, and serving systems across the company, partnering with Data Science and Product Engineering to power data-driven product decisions.

You will own core data pipelines, optimize lakehouse infrastructure, and mentor engineers. This role offers remote work flexibility, competitive equity, and comprehensive benefits.

Qualifications

• 4+ years of software engineering with data infrastructure and distributed systems.
• Strong Python and SQL proficiency with hands-on Spark experience.
• Experience with modern cloud data stacks (AWS, Databricks, Airflow).
• Familiarity with data-versioning, lineage, partitioning, and data lakehouse concepts.

Responsibilities

• Design and build scalable data pipelines and lakehouse infrastructure on AWS using PySpark, Databricks, and Airflow.
• Improve data platform experience with self-service tooling and clear documentation.
• Own data pipelines and models powering dashboards, ML models, and customer-facing products.
• Manage Databricks workspaces, access, performance, and high availability of pipelines.
• Lead data quality, testing, observability, and cost optimization initiatives.
• Collaborate with Data Science and Product Engineering to enable data-driven decisions.

Skills

Python

SQL

Spark

AWS

Databricks

Airflow

Hadoop

Kafka

Tools

Terraform

Databricks

Trino/Presto

Job description

About Us

At Parafin, we're on a mission to grow small businesses.

Small businesses are the backbone of our economy, but traditional banks often don't have their backs. We build tech that makes it simple for small businesses to access the financial tools they need through the platforms they already sell on.

We partner with companies like DoorDash, Amazon, Worldpay, and Mindbody to offer fast and flexible funding, spend management, and savings tools to their small business users via a simple integration. Parafin takes on all the complexity of capital markets, underwriting, servicing, compliance, and customer service for our partners.

We're a tight-knit team of innovators hailing from Stripe, Square, Plaid, Coinbase, Robinhood, CERN, and more — all united by a passion for building tools that help small businesses succeed. Parafin is backed by prominent venture capitalists including GIC, Notable Capital, Redpoint Ventures, Ribbit Capital, and Thrive Capital. Parafin is a Series C company, and we have raised more than $194M in equity and $340M in debt facilities.

Join us in creating a future where every small business has the financial tools they need.

About The Position

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.

What You'll Do

• 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

• Salary Range: $220k-$265k
• Equity grant
• Medical, dental & vision insurance
• Work from home flexibility
• Unlimited PTO
• Commuter benefits
• Free lunches
• Paid parental leave
• 401(k)
• Employee assistance program