Title: Senior to Expert-level Data Engineer
Location: 100% Remote
Tiem Zone: CST
Hours: Approximately 50 hours/week
Type: Direct hire
Salary range: 180 – 220K
Job Description: We are looking for a senior to expert-level Data Engineer who will play a key role in accelerating innovation by delivering robust data solutions. You will be responsible for designing and implementing a scalable GCP-native data strategy that underpins our machine learning initiatives and enables decentralized, squad-owned data infrastructure. Working closely with industry-leading engineers and scientists, you will help achieve large-scale behavior change through intelligent, data-powered systems. Your work will involve crafting reusable, high-fidelity data products and building infrastructure that allows for rapid iteration, continual improvement, and measurable outcomes.
Requirements:
- 8+ years of professional experience in data engineering or a related field, with demonstrated expertise in building and deploying scalable data solutions
- Strong skills in critical thinking, decision making, problem-solving, and attention to detail
- Technically skilled, and able to understand technology tradeoffs that your squad will face
- Proficient at resolving ambiguity. When there is uncertainty, you can work with squad colleagues to define the path forward
- Able to work independently, operating without significant input or guidance
- Expert-level proficiency in Python and SQL for scalable data transformation and strategic analysis within the squad's domain
- Expertise in designing, building, and operating data products, not just pipelines, that deliver compounding value and adhere to domain-driven data principles
- Architect and govern the data storage strategy within the squad, strategically utilizing transactional systems (e.g., AlloyDB), Operational Data Stores (ODS), and analytical data warehouses, with a primary focus on BigQuery
- Mastery of Google BigQuery for strategic data product development and high-volume analytical processing, coupled with deep hands-on experience integrating with transactional databases such as AlloyDB (PostgreSQL) and Cloud SQL (PostgreSQL)
- Experience modernizing legacy data assets and optimizing high-performance SQL/procedural logic, including exposure to proprietary SQL dialects (e.g., TSQL, PL/pgSQL), demonstrating an ability to decouple logic from operational databases to BigQuery/Dataform
- Extensive experience architecting ingestion strategies using native services like Pub/Sub and Datastream (CDC) for high-throughput data delivery
- Mandatory deep expertise in the strategic native GCP stack: GCP Data Ecosystem: including Dataform for transformations, Cloud Composer (Airflow) for orchestration, and Cloud Dataflow (Apache Beam) for processing
- Experience applying Dataplex features for data governance, quality, and discovery across the domain's data products
- Proven success collaborating across engineering, product, and science teams to deliver squad-owned data products in a fast-paced, iterative environment
- Highly motivated and organized, demonstrating an advanced ability to influence technical direction and build effective partnerships across internal and external stakeholders
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