WhyHireWrong?

Compensation

Full Description

The Role This is a hands on data engineering position embedded in a product focused environment. The work spans the full data lifecycle: gathering requirements from stakeholders, designing technical solutions, and shipping reliable, scalable pipelines. Expect close collaboration with data architects, asset managers, and product managers. This role sits at the intersection of engineering and business outcomes. What the Work Looks Like Day to Day Translate product and business requirements into technical data solutions Design and implement data pipelines and capabilities across product offerings Work with data architects to ensure solutions are aligned with broader technical strategy Identify gaps in internal processes and lead improvements Write clean, reusable code that adheres to established engineering standards Communicate technical decisions clearly to both technical and non technical audiences Technical Stack The primary environment is Google Cloud Platform. Day to day tooling includes: BigQuery for data analysis and processing Cloud Composer / Airflow for workflow orchestration Dataproc / PySpark for large scale data processing Vertex AI for machine learning adjacent workloads Cloud Spanner and Cloud Run for additional platform needs Python as the primary programming language, with GitHub Copilot integrated into the workflow What's Required Degree in Computer Science, Engineering, or a related field, or equivalent demonstrated experience Proven background in data engineering and architecture, including ownership of strategic technical initiatives Strong Python skills with hands on experience across the GCP services listed above Familiarity with PySpark and big data processing patterns Ability to explain complex technical concepts to varied audiences Comfortable working in fast moving environments where priorities shift What Sets a Strong Candidate Apart A track record of not just building pipelines, but improving how a team builds them: process thinking alongside technical depth. No need to be an expert in every tool listed. Intellectual curiosity and a structured approach to learning matter more than a perfect checklist match.