Data Engineer

Cline • Full-time • San Francisco, CA, US • 16h ago

Who We Are

With over 3.2M+ installs and 50k+ GitHub stars, Cline is the leading open-source AI coding agent. Trusted by the world's largest engineering organizations and individual developers alike, Cline is model agnostic, provider agnostic, and IDE agnostic, meeting engineers everywhere they work while keeping code on your infrastructure. Teams choose Cline because it's the only coding agent that combines cutting-edge capability with enterprise-grade security, using existing provider contracts directly with zero markup. Cline has raised $32M in combined Series A and Seed funding, led by Emergence Capital and Pace Capital, with participation from 1984 Ventures, Essence VC, and Cox Exponential.

What We Are Looking For

We’re looking for a Data Engineer who thrives in building robust, scalable data systems that power machine learning, analytics, and product intelligence. You’ll help design the data backbone that enables our business to grow and our AI to learn, reason, and create.

As a Data Engineer, you’ll play a critical role in designing, building, and optimizing data pipelines that fuel our AI models and insights. You’ll work closely with machine learning engineers, backend developers, and product teams to ensure our data infrastructure is reliable, secure, and high-performing.

You’ll work across the entire data lifecycle — from ingestion and transformation to orchestration and monitoring — to support our fast-evolving AI systems.

Responsibilities

Design, build, and maintain scalable data pipelines for training and deploying AI models.
Develop efficient ETL / ELT workflows using modern data tools (e.g., Airflow, dbt, Dagster).
Manage structured and unstructured data sources — from product telemetry to code datasets.
Work closely with product and business teams to ensure that our data supports the insights they need.
Work closely with ML engineers to deliver clean, high-quality datasets for model training.
Implement best practices for data governance, lineage, and quality control.
Collaborate with infrastructure and DevOps to ensure data reliability and performance at scale.
Optimize data storage and compute costs across cloud environments (AWS / GCP / Azure).
Contribute to internal data tooling and automation that make our data stack faster and smarter.

Qualifications

3–6+ years of experience as a Data Engineer or similar role in data infrastructure.
Strong experience with Python, SQL, and data pipeline orchestration tools.
Deep understanding of data modeling, warehousing, and distributed systems.
Hands-on experience with modern data stacks (e.g., Snowflake, BigQuery, Redshift, Spark, Databricks).
Familiarity with ML pipelines and model data requirements (preferred).
Experience with cloud platforms (AWS / GCP / Azure) and infrastructure-as-code (Terraform, CloudFormation).
Strong analytical mindset, bias for automation, and ownership of data reliability.

Our cash compensation range for this role is $190- $210,000+.

Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.

Equity: In addition to the base salary, equity may be part of the total compensation package.

Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.