Data Engineer

Motorola Solutions•Los Angeles, CA

12d•Onsite

About The Position

Silvus Technologies, a wholly owned subsidiary of Motorola Solutions, is seeking a Data Engineer for its Business Intelligence team. Reporting to the Director of Operations, this role designs, builds, and maintains the modern data warehouse and scalable pipelines that support business intelligence and analytics. The Data Engineer ensures data architecture is optimized for performance, scalability, and reliability by evolving data models, monitoring pipeline health, and implementing infrastructure that supports long-term business growth. The position is 100% onsite, Monday through Friday, at Silvus Technologies’ headquarters in West Los Angeles, California. The role may also include lifting equipment weighing up to 15 pounds to set up demonstrations and testing. Travel is not required.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, or Mathematics and at least 3 years of database engineering experience, or a high school diploma and at least 7 years of database engineering experience.
Expertise in SQL and data warehousing, such as Snowflake, BigQuery, or PostgreSQL.
Strong programming skills in Python or Scala for data orchestration, such as Airflow or dbt.
Experience with API integrations and managing unstructured and structured data.
Background in database administration and performance tuning.
Must be a U.S. Person (U.S. citizen or U.S. permanent resident) due to clients under U.S. federal contracts.
Employment is contingent upon successfully clearing a background check and drug test.

Nice To Haves

Master’s degree in Computer Science, Data Engineering, or Mathematics.
Experience with non-relational databases or data stores, including object storage, document or key-value stores, graph databases, or column-family databases.
Experience modernizing pipelines to reduce technical debt and improve reliability.
Strong written and verbal communication skills and comfort working independently in ambiguous problem spaces.
Experience building a database from the ground up.

Responsibilities

Design, build, and extend the core data warehouse using platforms such as Snowflake, BigQuery, or Redshift.
Design physical and logical data structures optimized for high-volume ingestion and rapid analytical queries.
Manage the evolution of data schemas as backend and CRM features are added, preserving historical integrity and system performance.
Evaluate and implement appropriate modern data-stack tools, compute tiers, and storage solutions to support growth without requiring a complete rebuild.
Design, build, and optimize scalable ETL/ELT pipelines that move data from various sources into the data warehouse.
Monitor pipeline health and data integrity, and alert the team to discrepancies before they reach the reporting layer.
Perform other related duties as assigned.