Senior Software Engineer, Data Platform

About our client

Our client is a Seed-stage AI company (recently closed a $25M round led by a tier-one VC) building autonomous growth agents for the $1T performance marketing industry. Founded in 2024 by veterans of major ad-platform and e-commerce companies, led by a CEO who was previously a VP of Engineering at a major consumer-tech company, they bring the growth technology of the largest platforms to every business. A fast-growing network of D2C brands and apps already relies on their agents, with SMB customers seeing a 40% lift and a waitlist growing by the day. The team is around 25 people, backed by tier-one investors, and well-funded with multiple years of runway.

The role

As a Software Engineer on the Data Platform, you will be a foundational member of the team, owning the data infrastructure that powers the company's autonomous AI agents. This is a true builder's seat: you will design the pipelines, models, and standards the entire product depends on.

What you'll do

• Own and evolve the data platform across batch and streaming pipelines, ensuring scalability, reliability, and performance.

• Design and maintain robust ETL/ELT processes that integrate data from diverse sources, including major marketing and advertising platforms.

• Define and standardize core data models, base tables, and schemas for consistency across analytics and ML applications.

• Implement strong data governance, access control, and security practices to protect sensitive business and customer data.

• Build and maintain real-time streaming infrastructure to power event-driven systems and business insights.

• Partner with ML engineers, marketing ops, and product teams to guarantee data availability and quality.

• Develop monitoring, alerting, and validation frameworks that keep data accurate and pipelines reliable.

What we're looking for

• 3 to 6 years of software engineering experience, ideally at a senior level, building data platforms and infrastructure (a software engineer who has worked on data, not a career data engineer).

• Strong experience with batch and/or streaming pipelines using modern frameworks such as Spark, Beam, Flink, Kafka, or Pub/Sub.

• Proficiency with SQL and hands-on experience designing data schemas for analytical and operational use.

• Experience with data warehouses and lakes (BigQuery, Snowflake, Redshift, or similar) and strong programming skills in Python, Java, or Scala.

• Solid understanding of data security, compliance, and governance, plus experience on a major cloud platform (GCP, AWS, or Azure).

• A track record at a high-growth tech company or reputable VC-backed startup.

Bonus points

• Hands-on experience with real-time streaming and event-driven architectures.

• Familiarity with workflow orchestration (Airflow) and distributed storage systems (Bigtable, HBase, Cassandra).

• Experience building marketing data pipelines (GAQL, Ads APIs) or supporting ML feature stores.

• Contributions to open-source data engineering projects.

Compensation and benefits

• Base salary of $160K to $225K, plus competitive equity.

• Visa sponsorship available, including H1B transfers.

Location and work model

• On-site in Mountain View, CA, with hybrid flexibility for candidates based in San Francisco or with a longer commute.