[Hiring] Senior AI/Data Engineer @WorkWave

Role Description

We’re looking for a customer-centric Senior AI/Data Engineer to build and scale data systems that drive our “decision intelligence” products. You’ll work at the intersection of data engineering, product development, and AI/ML enablement—designing systems that empower customer-facing data products. This role requires not only deep technical expertise but also a strategic mindset, strong communication skills, and a high sense of ownership over how data supports the business. You will collaborate across teams to ensure data is a true product enabler.

WHAT YOU'LL DO:

• Engineering & AI Enablement
  • AI/ML ownership: Build trusted AI/ML predictions and forecasts via feature pipelines, model input/output data flows, and robust data validation frameworks.
  • Pipeline Design: Design and implement reliable, scalable, and secure data pipelines that serve analytical and product use cases.
  • Leadership: Provide technical leadership and mentorship to other data engineers and cross-functional collaborators, fostering a culture of engineering excellence.
• Ecosystem Ownership & Strategy
  • Architecture & Evolution: Own the architecture and evolution of our data platform, ensuring it meets the performance, scalability, and agility needs of our growing business.
  • Governance & Observability: Implement data governance, quality, and observability best practices to ensure trustworthy insights, proactively managing data health before it impacts the business.
  • Infrastructure Optimization: Optimize cloud data infrastructure for cost, performance, and maintainability, treating the platform as a product rather than just a utility.
• Collaboration & Translation
  • Cross-Functional Partnership: Collaborate closely with product managers, engineers, and customer stakeholders to understand context and needs, and help translate them into engineering solutions.
  • Customer-Centricity: Ensure engineering efforts are aligned with delivering clear business value and enhancing the customer experience.

Qualifications

• 5+ years of experience in data engineering, with 1–2+ years in a senior or lead capacity.
• Deep understanding of ML models and the ability to articulate trade-offs between different architectures.
• "Ninja-level" proficiency in Python for complex data structures and automation, alongside strong SQL expertise.
• Strong familiarity with Scikit-Learn and similar libraries, with specific experience building and maintaining associated feature engineering pipelines.
• High proficiency in MLOps practices and orchestration tools (e.g., Airflow, dbt, Dagster).
• Solid experience with modern data platforms (e.g., Snowflake, BigQuery, Redshift, or Databricks).
• Strong understanding of data modeling, performance optimization, and cloud computing (AWS, GCP, or Azure).
• Excellent communication and collaboration skills, with a proven ability to work effectively across technical and non-technical teams.

Requirements

• $160,000 - $180,000 a year.
• Final offer will depend on various factors, including the candidate's qualifications, relevant experience, and the organization's budget.
• Salary estimates from websites may not accurately reflect the actual salary range for the position.

Benefits

• Robust benefits package, including health and dental and 401k with company match.
• Flexible Time Off policy or generous PTO plan (role dependent) and paid holidays.
• Up to 4 weeks paid bonding leave.
• Tuition reimbursement.
• Robust Employee Assistance Program through TotalCare offering free counseling 24/7/365.
• 24/7 access to virtual medical care with Teladoc.
• Quarterly awards based on peer nominations.
• Regional discounts and perks.
• Opportunities to participate in charitable events and give back to the community.