Hands-On Data Architect

About the Role

We are looking for a Hands-On Data Architect to lead the design and implementation of modern data platforms across AWS and GCP.

This is a high-impact, hands-on role — you will help shape architecture decisions and bring them to life by building production systems, from data pipelines to APIs and serving layers.

You will work across a variety of projects and environments — including government and public-sector organizations, as well as startups, scale-ups, and enterprise clients. These environments differ in pace, constraints, and maturity, requiring the ability to adapt your approach, architecture, and communication style to each context.

What You’ll Do

• Design and deliver end-to-end data architecture across diverse client environments

• Lead the design and contribute to the implementation of data pipelines, lakehouses, and data warehouses (batch & streaming), taking a hands-on role when needed or supporting engineering teams

• Define and guide data transformation approaches using tools such as dbt, Dataform, and Spark, while collaborating closely with those implementing them

• Help shape and support the implementation of serving layers, including APIs and microservices (e.g., Cloud Run, ECS), either directly or by working alongside delivery teams

• Work hands-on with cloud-native technologies across AWS and GCP

Work Across Diverse Environments

• Deliver projects in regulated and policy-driven environments, balancing compliance and delivery

• Work with startups and enterprises, adapting to different scales, speeds, and expectations

• Contribute to AI-related and advanced analytics projects, enabling modern data use cases

Operate in Real-World Constraints

• Design systems that meet security, governance, and regulatory requirements

• Collaborate in environments where ownership and decision-making are shared across stakeholders

• Influence technical direction while navigating organizational and operational constraints

• Communicate effectively with both technical teams and non-technical stakeholders, including policy organizations

Engineering & Leadership

• Ensure systems are scalable, reliable, and cost-efficient

• Lead architecture discussions, design reviews, and technical best practices

• Mentor engineers and contribute directly to implementation

Requirements

• 7+ years of experience in data engineering / data architecture

• Proven experience designing and building production-grade data platforms

• Strong hands-on experience with AWS and/or GCP (experience with both is a strong advantage)

• Willingness to work on-site at least 3 days a week, from both HQ office and client locations.

• Fluent in both Hebrew and English

Cloud & Data Stack

• AWS: S3, Redshift, Glue, Lambda, ECS (or similar)

• GCP: BigQuery, Cloud Run, Dataflow, GCS (or similar)

• Experience with Databricks / Spark-based processing

Data & Engineering

• Strong SQL and Python skills

• Experience with dbt and/or Dataform

• Deep understanding of:Data modeling (warehouse & lakehouse)
  ETL / ELT patterns
  Batch and streaming architectures

• Experience building APIs / backend services for data access

• Familiarity with CI/CD, testing, and production systems

Adaptability & Stakeholder Engagement

• Experience working across different types of organizations — or strong ability to adapt

• Ability to navigate complex stakeholder environments and constraints

• Strong communication skills — able to bridge engineering, business, and policy stakeholders

What Makes You a Great Fit

• You think like an architect but build like an engineer

• Comfortable moving between:Structured, regulated environments
  Fast-moving, ambiguous product environments

• Able to adapt solutions to the customer, rather than applying a one-size-fits-all approach

• Strong ownership mindset — even in environments with shared responsibility

• Pragmatic decision-maker who balances ideal architecture with real-world constraints

• Clear communicator who can explain complex systems simply

Nice to Have

• Experience with multi-cloud architectures

• Familiarity with BI tools (Looker, Tableau, Power BI, QuickSight)

• Experience with data governance, security standards, and PII handling

• Background in software engineering beyond data (microservices, APIs)

AI / Advanced Analytics (Advantage)

• Experience integrating AI/ML capabilities into data platforms

• Familiarity with LLM-based applications, ML pipelines, or real-time inference systems

• Experience with tools such as Vertex AI, SageMaker, or similar

• Understanding of how to design data architectures that support AI use cases

Why Join Us

• Work across a diverse set of projects and industries

• Solve real-world problems with real constraints, not just theoretical architecture

• Opportunity to influence and deliver in complex, multi-stakeholder environments

• Modern stack across AWS and GCP

• Engineering-driven culture with strong ownership