Staff Software Engineer - Data
Company: DoubleVerify
Location: San Diego
Posted on: January 12, 2026
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Job Description:
We are looking for a Staff Software Engineer to shape the future
of our data platform with a focus on small data at scale. While
many companies over-index on heavyweight distributed systems, we
believe in the power of efficient, local-first, columnar engines
like DuckDB to process and analyze data quickly, reliably, and
cost-effectively. As a Staff Software Engineer, you will set the
technical direction for how our teams ingest, transform, and serve
data, bridging the gap between lightweight embedded tools and
cloud-scale systems. You’ll be hands-on in building pipelines,
while also mentoring engineers and setting best practices across
the organization. What You’ll Do • Architect and Build Data
Pipelines o Design and implement data processing workflows using
DuckDB, Polars, and Arrow/Parquet. o Balance small-data local
pipelines with cloud data warehouse backends (Snowflake etc). •
Champion the Small Data Mindset o Advocate for efficient,
vectorized, local-first approaches where appropriate. o Drive best
practices for designing reproducible and testable data workflows. •
Collaborate Cross-Functionally o Partner with data science,
professional services, and product engineering teams to define
semantic data layers. o Provide technical leadership in how data is
versioned, validated, and surfaced for downstream use. •
Operational Excellence o Establish standards for CI/CD,
observability, and reliability in data pipelines. o Automate
workflows and optimize data layout for performance and cost
efficiency. • Mentor & Lead o Serve as a thought leader in the
organization, guiding engineers on when to use lightweight tools
vs. distributed platforms. o Mentor senior and mid-level data
engineers to accelerate their growth. Who You Are • Core Technical
Skills o Deep expertise in SQL (window functions, CTEs,
optimization). o Strong Python skills with data libraries. o
Proficiency with DuckDB (extensions, parquet/iceberg integration,
embedding in pipelines). o Hands-on with columnar formats (Parquet,
Arrow, ORC) and schema evolution. o Expertise in Kubernetes and
Helm • Infrastructure & Tools o Cloud storage experience (AWS S3,
GCS). o Experience with semantic layer frameworks (CubeJS). o CI/CD
tooling (GitHub Actions, Terraform, Docker/Kubernetes). •
Leadership o Track record of leading architecture decisions and
mentoring teams. o Ability to set standards for maintainability and
developer experience. Nice to Haves • Experience with serverless
and embedded analytics (DuckDB WASM, in production). • Exposure to
data versioning (Delta Lake, Iceberg, Hudi). • Knowledge of ML/LLM
data prep workflows and vector database integrations. • Previous
experience building hybrid stacks (local development cloud
warehouse production). What Success Looks Like • Data pipelines
that are fast, simple, and reproducible—running in seconds or
minutes, not hours. • A team that defaults to the right level of
tooling for the problem (small-data-first, scale-up only when
necessary). • Clear semantic data definitions that power analytics,
experimentation, and AI/ML initiatives. • Reduced infrastructure
cost and complexity without sacrificing reliability. The successful
candidate’s starting salary will be determined based on a number of
non-discriminating factors, including qualifications for the role,
level, skills, experience, location, and balancing internal equity
relative to peers at DV. The estimated salary range for this role
based on the qualifications set forth in the job description is
between [$128,000 - $230,000]. This role will also be eligible for
bonus/commission (as applicable), equity, and benefits. The range
above is for the expectations as laid out in the job description;
however, we are often open to a wide variety of profiles, and
recognize that the person we hire may be more or less experienced
than this job description as posted.
Keywords: DoubleVerify, Rowland Heights , Staff Software Engineer - Data, Engineering , San Diego, California
