Sr. Data Engineer

Arlo•Milpitas, CA

14h•$115,000 - $155,000•Hybrid

About The Position

At Arlo, we're passionate about creating innovative and reliable solutions that help people protect what matters most to them. Our team is dedicated to delivering products that exceed our customers' expectations, while always pushing the boundaries of what's possible in the world of protection technology. We believe that everyone deserves to feel safe and secure, whether they're at home or away, and we're committed to providing our customers with the peace of mind they need to live their lives without worry. Arlo’s deep expertise in AI- and CV-powered analytics, cloud services, user experience, product design, and innovative wireless and RF connectivity enables the delivery of a seamless, smart security experience for Arlo users that is easy to set up and interact with every day. Senior Data Engineer – Partner Metrics & Business Insights Location: Milpitas, CA (hybrid) We are seeking a Data Engineer with strong analytics and business insight — or a Data Analyst with strong engineering skills — to build trusted metrics, scalable data pipelines, and curated datasets used by both internal teams and external partners. This role focuses on transforming business logic, device telemetry, backend events, and AI-generated signals into trusted, decision-ready data products. This is not a pure pipeline role. Success requires strong judgment around metric definitions, data quality, and delivering partner-facing data with a customer-obsessed mindset.

Requirements

3–5+ years of experience as a Data Engineer, Analytics Engineer, or in a similar data-focused role.
Strong proficiency in SQL and experience building analytics-ready data models.
Hands-on experience with Databricks or similar cloud lakehouse platforms, including strong proficiency with SQL-based transformations.
Deep understanding of BI and analytics concepts, including metric definitions, dimensional modeling, and report-ready datasets.
Demonstrated ability to interpret existing reporting logic and translate it into scalable, production-grade pipelines.

Nice To Haves

Experience working with Tableau data sources (TDS/TDSX), published extracts, or equivalent BI artifacts.
Experience with ETL / orchestration tools such as Databricks Workflows , dbt, Airflow, or similar.
Familiarity with external or third-party data sharing technologies and requirements (e.g., Delta Sharing / DeltaShare or similar partner data export mechanisms).
Experience delivering data products to external customers or partners.
Background in SaaS, subscription, IoT, or consumer electronics environments.

Responsibilities

Data Engineering & Pipelines Design and maintain production-grade pipelines ingesting telemetry, backend events, and AI signals.
Translate legacy BI logic (e.g., Tableau sources) into governed SQL transformations.
Build ETL / ELT workflows in Databricks and ensure SLA-driven freshness and reliability.
Metrics & Data Modeling Define and maintain core product, device, and service metrics.
Translate business requirements into precise metric definitions and durable data models.
Build report-ready facts and dimension models ensuring semantic consistency.
Partner & Cross-Functional Collaboration Serve as technical contact for partner data questions.
Work with Product, BI, AI/ML, Platform, and Finance to align data outputs to business needs.
Clearly communicate assumptions, risks, and tradeoffs.
Data Quality & Governance Own end-to-end data correctness.
Implement validation, reconciliation, monitoring, and documentation standards.
Operational Excellence Improve pipeline reliability, performance, and maintainability.
Reduce manual effort and contribute to data engineering best practices.