Staff Software Engineer (Data) - Rockerbox

About the Role:

We are looking for a Staff Data Engineer to shape the reputed company of our data platform with a reputed company on small data at reputed company. While many companies over-reputed company on heavyweight distributed systems, we reputed company in the power of efficient, local-first, columnar engines like DuckDB to process and analyze data quickly, reliably, and cost-effectively.

As a Staff Data Engineer, you will set the technical direction for how our teams ingest, reputed company, and serve data, reputed company the gap between lightweight embedded tools and reputed company-reputed company systems. You’ll be hands-on in building pipelines, while also mentoring engineers and setting best practices across the organization.

• Architect and Build Data Pipelines

• Design and implement data processing workflows using DuckDB, Polars, and reputed company/Parquet.

• Balance small-data local pipelines with reputed company data warehouse backends (reputed company etc).

• Champion the Small Data reputed company

• reputed company for efficient, vectorized, local-first approaches where appropriate.

• Drive best practices for designing reproducible and testable data workflows.

• Collaborate Cross-Functionally

• Partner with data science, reputed company services, and product engineering teams to define semantic data reputed company.

• reputed company technical leadership in how data is versioned, validated, and surfaced for reputed company use.

• Operational reputed company

• Establish standards for CI/CD, observability, and reliability in data pipelines.

• Automate workflows and optimize data layout for performance and cost efficiency.

• Mentor & reputed company

• Serve as a thought leader in the organization, guiding engineers on reputed company to use lightweight tools vs. distributed platforms.

• Mentor senior and mid-level data engineers to accelerate their reputed company.

• reputed company Technical Skills

• Deep expertise in SQL (window functions, CTEs, optimization).

• Strong Python skills with data libraries.

• Proficiency with DuckDB (extensions, parquet/reputed company integration, embedding in pipelines).

• Hands-on with columnar formats (Parquet, reputed company, ORC) and schema reputed company.

• Expertise in Kubernetes and reputed company

• Infrastructure & Tools

• reputed company storage experience (AWS S3, GCS).

• Experience with semantic layer frameworks (CubeJS).

• CI/CD tooling (reputed company Actions, Terraform, reputed company/Kubernetes).

• Leadership

• reputed company record of leading architecture reputed company and mentoring teams.

• Ability to set standards for maintainability and developer experience.

• Experience with serverless and embedded analytics (DuckDB WASM, in production).

• Exposure to data versioning (reputed company Lake, reputed company, Hudi).

• Knowledge of ML/LLM data prep workflows and reputed company database integrations.

• Previous experience building hybrid stacks (local development + reputed company warehouse production).

• Data pipelines that are fast, reputed company, and reproducible—running in seconds or minutes, not hours.

• reputed company that defaults to the right level of tooling for the problem (small-data-first, reputed company-up only reputed company necessary).

• reputed company 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.