Motion Recruitment
Data Analytics Engineer / Security / Los Angeles (Hybrid)
Motion Recruitment, Los Angeles, California, United States, 90079
Our client is a fast-growing technology company operating at the intersection of IoT, enterprise software, and real-time data intelligence. Known for fostering a culture of innovation, inclusivity, and collaboration, the organization is modernizing how businesses protect assets, optimize operations, and gain actionable insights from complex data environments.
With strong backing and a mission-driven team, the company continues to invest heavily in building scalable, data-driven solutions that have a measurable impact on customers. As part of its growth, the firm is seeking an Analytics Engineer to transform how data is leveraged across its platform.
This role combines the technical rigor of data engineering with the practical impact of business intelligence, offering the opportunity to own foundational data models while supporting dashboards and reporting frameworks that power decision-making across product, engineering, and customer-facing teams. You will work closely with both internal stakeholders and clients to design pipelines, optimize analytics frameworks, and extract insights from diverse sources such as IoT telemetry, application logs, and relational databases.
Responsibilities
Build and evolve BI and semantic layer datasets powering analytics across the business Translate requirements into efficient data pipelines, dashboards, and frameworks Transform and model data from diverse sources including IoT streams and application logs Conduct deep-dive analyses to improve system performance and product capabilities Empower teams with training, best practices, and data literacy initiatives Collaborate cross-functionally to align data solutions with business needs Requirements
4+ years in analytics or data engineering with strong SQL and Python skills Solid grasp of database design, data modeling, and building scalable ETL/ELT pipelines Hands-on experience with BI/visualization tools (e.g., Tableau, QuickSight, Sigma) Familiarity with cloud platforms (AWS preferred), data warehouses, and infrastructure-as-code tools Comfortable working with real-time or high-volume data (IoT, telemetry, streaming) in fast-paced environments What We Offer
Equity Incentive Plan Medical, Dental, and Vision Insurance 401k with Company Match Generous PTO and family-friendly culture Opportunity to shape analytics practices within an emerging, high-growth industry Applicants must be currently authorized to work in the US on a full-time basis now and in the future. We are an equal opportunities employer and welcome applications from all qualified candidates.
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Build and evolve BI and semantic layer datasets powering analytics across the business Translate requirements into efficient data pipelines, dashboards, and frameworks Transform and model data from diverse sources including IoT streams and application logs Conduct deep-dive analyses to improve system performance and product capabilities Empower teams with training, best practices, and data literacy initiatives Collaborate cross-functionally to align data solutions with business needs Requirements
4+ years in analytics or data engineering with strong SQL and Python skills Solid grasp of database design, data modeling, and building scalable ETL/ELT pipelines Hands-on experience with BI/visualization tools (e.g., Tableau, QuickSight, Sigma) Familiarity with cloud platforms (AWS preferred), data warehouses, and infrastructure-as-code tools Comfortable working with real-time or high-volume data (IoT, telemetry, streaming) in fast-paced environments What We Offer
Equity Incentive Plan Medical, Dental, and Vision Insurance 401k with Company Match Generous PTO and family-friendly culture Opportunity to shape analytics practices within an emerging, high-growth industry Applicants must be currently authorized to work in the US on a full-time basis now and in the future. We are an equal opportunities employer and welcome applications from all qualified candidates.
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