Sr Data Product Engineer

As a Senior Data Product Engineer, you will play a critical role in the end-to-end lifecycle of our data products. You'll blend deep data engineering expertise with a keen product mindset, architecting and building reusable data assets that meet the needs of diverse internal consumers, from business analysts to data scientists.

You'll be at the forefront of implementing cutting-edge cloud technologies and data modeling techniques to ensure our data infrastructure is robust, performant, and future-proof. This role is for someone who loves to build, optimize, and drive tangible value from data.

What You'll Do

• Design & Build Data Products: Lead the full lifecycle development of data products, including requirements gathering, architectural design, implementation, testing, and deployment. Ensure data products are discoverable, well-documented, and adhere to strict data quality standards.
• Strategic Data Modeling: Apply a pragmatic combination of Domain-Driven Design (DDD) principles to deeply understand core business contexts and translate them into robust, Kimball-inspired dimensional models that power our data products within Snowflake.
• Real-time Data Processing: Architect and implement highly efficient, event-driven data pipelines using AWS Kinesis for data ingestion and stream processing, leveraging AWS Lambda for serverless transformations and real-time data delivery.
• Advanced Data Transformation: Develop, optimize, and maintain complex SQL-based data transformations using dbt (Data Build Tool) within our Snowflake data platform, ensuring modularity, testability, and version control for all data models.
• AI/ML Data Enablement: Collaborate closely with our AI/ML workbench to design and build data products specifically tailored for machine learning initiatives, including feature engineering, data preparation, and ensuring data readiness for model training and inference.
• Operational Excellence: Establish and enforce best practices for data governance, metadata management, data lineage, and data observability to ensure the reliability and integrity of our data products.

What You'll Bring

• Experience: 5+ years of hands-on experience in data engineering, data warehousing, or a similar role, with a strong focus on building scalable and robust data solutions.
• Technical Prowess:
• Expert-level proficiency with Snowflake for data warehousing, performance tuning, and query optimization.
• Proficiency in SQL, Java, dbt (Data Build Tool) and modern data platforms (Snowflake, AWS, GCP) for data modeling, transformation, testing, and documentation.
• Extensive experience with AWS Lambda and AWS Kinesis for serverless and real-time data processing architectures (CI?CD).
• Strong programming skills in Python (preferred) for data manipulation, scripting, and automation.
• Proven experience in designing and preparing data for AI/ML applications.
• Data Modeling & Architecture: Deep practical understanding and application of both Kimball's dimensional modeling methodologies and Domain-Driven Design (DDD) concepts in complex data environments.
• Product Mindset: A genuine passion for treating data as a product, understanding user needs, defining data contracts, and delivering measurable value through high-quality data assets.
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• Education: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field.

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The hiring range for this position in Washington is $145,500 to $195,00 per year and in California is $138,900 to $186,200 per year based on a 40 hour work week. The amount of hours scheduled per week may vary based on business needs. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.