Data Analytics Architect

abra professional services is seeking a Data Analytics Architect / Principal Data Engineer.

We are looking for a skilled Data Analytics Architect / Principal Data Engineer to lead the organization’s analytics data domain, design large-scale data architecture, build advanced analytical models, define organizational data modeling standards, and implement innovative AI and LLM-based technologies.

This role requires deep expertise in data engineering, analytics, BI, SQL, PostgreSQL, data modeling, performance optimization, data governance, and the integration of AI tools into data engineering processes.

A full-time hybrid position based in Central Israel. The first 4–6 months will be based in Tel Aviv, followed by a transition to the Lod area. The position includes 1 day a week remote.

Key Responsibilities:

• Design and develop data architecture that supports large-scale analytics and business intelligence.

• Lead the design and implementation of complex data models and enterprise data modeling solutions.

• Define organizational standards, methodologies, and best practices in the data domain.

• Optimize database performance, analytical queries, and reporting processes.

• Lead LLM-based development and implement AI tools within data engineering processes.

• Mentor data engineers, conduct code reviews and architecture reviews.

• Collaborate with management and business stakeholders to build a technological roadmap.

• Establish frameworks for data quality and data governance.

• Lead initiatives to improve the reliability and stability of BI and analytics systems.

• Evaluate new technologies and lead the adoption of innovative solutions across the organization.

• Lead the design and implementation of end-to-end analytics platforms.

Requirements

Requirements:

must have requirements:

• Bachelor’s degree in Computer Science, Data Science, Statistics, or another relevant field, or equivalent professional experience.

• At least 5 years of experience in Data Engineering, with a focus on Analytics and BI.

• Expert-level SQL skills.

• Deep experience with PostgreSQL, including performance tuning and optimization.

• At least 3 years of experience with Python for data processing, automation, and testing.

• At least 3 years of experience designing and implementing large-scale data models.

• Experience leading performance optimization in complex data systems.

• Experience establishing and implementing Data Governance and Data Quality processes.

• Proven ability to translate business requirements into data architecture and technological solutions.

• Experience providing technical leadership, mentoring, and leading technological initiatives.

• Experience building Data and Analytics platforms from scratch.

• Proven experience integrating AI and LLM tools into development and data engineering processes.

Advantages:

• Experience in FinTech or financial organizations.

• Deep familiarity with regulation, information security, and compliance requirements.

• Experience working with Data Lakes and Data Warehouses.

• Experience with orchestration tools and ELT / ETL processes.

• Experience working in cloud environments such as AWS, GCP, or Azure.

• Familiarity with streaming technologies and real-time data processing.

• Experience leading technology teams or professional excellence groups.

Personality requirements:

• Fast learning ability and curiosity for new technologies and methodologies.

• Strategic thinking and broad system-wide perspective.

• Ability to lead and influence without formal authority.

• Ability to work independently and manage multiple tasks simultaneously.

• High personal responsibility and ability to receive professional feedback.

• Initiative, creativity, and ability to solve complex problems.

• High motivation and constant drive for excellence.

• Excellent interpersonal communication skills and ability to work with multiple stakeholders.

• Ability to drive organizational change and lead technological innovation.

Main interfaces:

• Reporting to a Team Lead / Department Lead.

• Direct work with business users, additional development teams within the organization, and QA teams.