Arlo
SeniorDataEngineer–DataFoundations
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“Senior Data Engineer – Data Foundations at Arlo. Skills: Data Engineering, Analytics Engineering, SQL, Databricks, Data Modeling, BI Concepts. 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”
What You'll Achieve.
Build trusted metrics, scalable data pipelines, and curated datasets used by both internal teams and external partners; Transform business logic, device telemetry, backend events, and AI-generated signals into trusted, decision-ready data products; Ensure SLA-driven freshness and reliability of data pipelines; Ensure semantic consistency of data models
What They're Looking For.
Must Have
4-6+ years of experience as a Data Engineer, Analytics Engineer, or in a similar data-focused role, Proficiency in SQL, Experience building analytics-ready data models, Hands-on experience with Databricks or similar cloud lakehouse platforms, 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 Have
Advanced degrees can be considered as part of this experience, 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
What You'll Do.
Design and maintain production-grade pipelines ingesting telemetry
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
Partner with the Data Analytics team to define and maintain core product
Translate business requirements into ‘Bronze layer’ data ingests that support metric definitions through durable data models
Build report-ready facts and dimension models and data pipelines to ensure semantic consistency
Own end-to-end data correctness and alerting
and documentation standards
Improve pipeline reliability
Reduce manual effort and contribute to data engineering best practices
How You'll Work.
Team & Collaboration
Partner with the Data Analytics team to define and maintain core product, device, and service metrics; Serve as technical contact for our partner data and product teams as required; Work with Product, BI, AI/ML, Platform, and Finance to align data outputs to business needs
Communication Scope
Clearly communicate assumptions, risks, and tradeoffs
Full Job Description
**About Arlo:** 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. Overview We are seeking a Data Engineer with strong analytics and business insight 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. ## **Key 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** * Partner with the Data Analytics team to define and maintain core product, device, and service metrics. * Translate business requirements into ‘Bronze layer’ data ingests that support metric definitions through durable data models. * Build report-ready facts and dimension models and dat
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