We are looking for an experienced and visionary Staff Data Architect to play a critical role in defining and shaping the data architecture for our flagship investigative analytics platform. In this position, you will design and guide the implementation of robust, scalable, and secure data pipelines that power advanced data processing for AI-driven insights as part of digital investigations.
You will work closely with cross-functional teams to drive technology alignment and ensure architectural excellence across multiple domains. This is a high-impact role, ideal for someone with deep technical expertise and strong strategic thinking, who thrives in a dynamic, collaborative environment and is passionate about building world-class technology platforms.
As our Data Architect, you will own the vision for how we manage, move, and leverage data within our SaaS product suite. Your role is pivotal in designing and implementing a robust data architecture that supports both real-time operational needs and advanced analytics, all within a scalable and cost-effective cloud-native environment.
Responsibilities:
Own the Data Vision: Take ownership of the data architecture, including our data lake, data warehouse, and ETL/ELT pipelines, to support our product teams and business intelligence.
Cost Optimization & Scalability: Provide architectural leadership and guidance to ensure our data platforms are designed for cost efficiency and scalability, actively identifying and implementing opportunities to optimize cloud spend.
Product-Centric Collaboration: Collaborate with engineering, product, data science, and security teams to translate product requirements and business needs into a strategic data architecture that drives product innovation.
Design & Governance: Conduct deep architecture reviews, assess technical risks, and provide recommendations to ensure data quality, security, and governance are embedded into every product.
Standardization & Enablement: Define and standardize data modeling practices, governance frameworks, and data pipeline patterns to enable efficient and consistent data development across product teams.
Technology Evolution: Evaluate new data technologies, tools, and methodologies (e.g., streaming platforms, modern data warehouses) to continuously improve our data platforms.
Documentation & Mentorship: Document architectural decisions, data flow diagrams, and cost models. Act as a mentor and technical authority, fostering a culture of technical excellence and cost-awareness.
You will work closely with cross-functional teams to drive technology alignment and ensure architectural excellence across multiple domains. This is a high-impact role, ideal for someone with deep technical expertise and strong strategic thinking, who thrives in a dynamic, collaborative environment and is passionate about building world-class technology platforms.
As our Data Architect, you will own the vision for how we manage, move, and leverage data within our SaaS product suite. Your role is pivotal in designing and implementing a robust data architecture that supports both real-time operational needs and advanced analytics, all within a scalable and cost-effective cloud-native environment.
Responsibilities:
Own the Data Vision: Take ownership of the data architecture, including our data lake, data warehouse, and ETL/ELT pipelines, to support our product teams and business intelligence.
Cost Optimization & Scalability: Provide architectural leadership and guidance to ensure our data platforms are designed for cost efficiency and scalability, actively identifying and implementing opportunities to optimize cloud spend.
Product-Centric Collaboration: Collaborate with engineering, product, data science, and security teams to translate product requirements and business needs into a strategic data architecture that drives product innovation.
Design & Governance: Conduct deep architecture reviews, assess technical risks, and provide recommendations to ensure data quality, security, and governance are embedded into every product.
Standardization & Enablement: Define and standardize data modeling practices, governance frameworks, and data pipeline patterns to enable efficient and consistent data development across product teams.
Technology Evolution: Evaluate new data technologies, tools, and methodologies (e.g., streaming platforms, modern data warehouses) to continuously improve our data platforms.
Documentation & Mentorship: Document architectural decisions, data flow diagrams, and cost models. Act as a mentor and technical authority, fostering a culture of technical excellence and cost-awareness.
Requirements:
Cloud-Native Data and Software Expertise: Strong background in building and managing SaaS data platforms on AWS, with deep, hands-on experience with services such as S3 as a Data Lake, Glue, Redshift, Kinesis, and Lambda.
Data Architecture: Deep understanding of data warehousing, data lakes, streaming architectures, and various data modeling techniques
AI/GenAI Architecture: Proven experience architecting data pipelines for AI and GenAI use cases. Knowledge of MLOps, feature stores, and vector databases
Cost Optimization Experience: Proven experience in cloud cost optimization for data platforms, including strategies for optimizing data storage, compute, and data transfer costs.
Data Technologies: Proficiency in big data technologies (e.g., Apache Spark, Kafka), and a strong coding background in Python and SQL for data manipulation and pipeline development.
SaaS Development Lifecycle: Solid understanding of CI/CD principles for data pipelines and how data architecture fits into a product-centric DevOps culture.
Soft Skills: Excellent communication and interpersonal skills – capable of influencing and aligning stakeholders at all levels, from engineers to business leaders.
Language Skills: Fluent in English (Hebrew – an advantage).
Domain Expertise: Background in digital investigations, cyber, or public safety domains – an advantage.
Cloud-Native Data and Software Expertise: Strong background in building and managing SaaS data platforms on AWS, with deep, hands-on experience with services such as S3 as a Data Lake, Glue, Redshift, Kinesis, and Lambda.
Data Architecture: Deep understanding of data warehousing, data lakes, streaming architectures, and various data modeling techniques
AI/GenAI Architecture: Proven experience architecting data pipelines for AI and GenAI use cases. Knowledge of MLOps, feature stores, and vector databases
Cost Optimization Experience: Proven experience in cloud cost optimization for data platforms, including strategies for optimizing data storage, compute, and data transfer costs.
Data Technologies: Proficiency in big data technologies (e.g., Apache Spark, Kafka), and a strong coding background in Python and SQL for data manipulation and pipeline development.
SaaS Development Lifecycle: Solid understanding of CI/CD principles for data pipelines and how data architecture fits into a product-centric DevOps culture.
Soft Skills: Excellent communication and interpersonal skills – capable of influencing and aligning stakeholders at all levels, from engineers to business leaders.
Language Skills: Fluent in English (Hebrew – an advantage).
Domain Expertise: Background in digital investigations, cyber, or public safety domains – an advantage.
This position is open to all candidates.
