Enterprise Security Technology Data Platforms  E ngineer Key Responsibilities Data Source Identification & Assessment: Identify, document, and assess data sources from various physical security systems (e.g., accesscontrol, video management, visitor management, incident management). Evaluate data structures, volume, quality, and integration options (APIs, direct DB access, file exports). Data Extraction & Ingestion: Design, develop, and implement robust data pipelines for extracting and ingesting data from diversesecurity systems into the data lake, ensuring secure and efficient data transfer. Data Transformation & Harmonization: Clean, normalize, and standardize disparate data formats. Harmonize data models to enable unifiedquerying and analysis across multiple systems. Data Enrichment: Integrate and enrich security data with contextual information from internal and external sources (e.g., HR data, organizational hierarchies, location metadata). Data Lake Integration: Ensure seamless integration of processed and enriched data into our existing data lakearchitecture. Maintain documentation on data schemas, lineage, and quality metrics. Documentation & Knowledge Transfer: Produce comprehensive documentation for all developed pipelines, transformation logic, and datamodels. Deliver knowledge transfer sessions to internal teams for ongoing maintenance and enhancement. Data Visualization & Reporting: Collaborate with security program stakeholders to design and develop dashboards and visualizations,identifying key metrics and creating intuitive, actionable reports. Data Privacy & Security: Adhere to data privacy regulations (e.g., GDPR, CCPA) and our internal data governancepolicies. Implement data minimization, anonymization, and robust access controls. Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or relatedfield (or equivalent experience). 5+ years of experience in data engineering, with a focus on ETL, data integration, or analytics platforms. Experience working with physical security or operational technology data sources is highly desirable. Experience pulling data from SaaS systems via APIs. Familiarity with the Genetec Security Center platform is desirable. Strong proficiency in building data pipelines and ETL workflows (e.g., using Python, SQL, Spark, Airflow, etc.). Hands-on experience with cloud data lake environments (e.g., AWS, Azure, GCP). Proven ability to design and implement data models for complex, heterogeneous data sources. Strong understanding of data privacy, security, and compliance best practices. Experience with data visualization tools (e.g., Tableau, Power BI, Looker) is a plus. Excellent documentation, communication, and collaboration skills. Pay Rate Range: $100-112/hr.