Staff Data Engineer – Data Modeling

Cloudinary

Career-pivot friendly

Who this role is best for

Aimed at senior data professionals who design complex data models and pipelines using SQL-heavy workflows and AWS technologies in Israel.

Best fit for

Senior data engineers with expertise in multi-stage pipeline design and optimization.
— “Design and own datasets across bronze, silver, and gold layers”
Professionals experienced in root cause analysis for business-critical data issues.
— “Own data correctness for key business metrics (e.g., ARR)”
Candidates comfortable with JSON and complex data inputs in pipeline development.
— “Work with complex data inputs (e.g., JSON, schemas, logs)”

Things to consider

Expectation to lead data modeling and transformation from raw to actionable datasets.
— “Lead the translation of business and product requirements into scalable data models”
Requires ongoing maintenance and optimization of existing data pipelines.
— “Optimize queries and data models for performance, scalability, and cost efficiency”

How to stand out

Showcase experience in developing AI-agents for data analysis acceleration.
— “Develop AI-agents to accelerate data analysis by internal and external users”
Highlight past collaborations with product managers and BI developers.
— “Collaborate closely with product managers, analysts, and BI developers”
Demonstrate expertise in SQL-heavy workflows and Airflow DAGs.
— “Develop and maintain SQL-heavy data pipelines and Airflow DAGs”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

developed scalable data models
optimized data pipelines
improved data quality

Typical background

data engineeringsoftware engineering

Skills & requirements

Required

Data ModelingETL ProcessesSQLAirflowAWSSnowflake

Preferred

AI DevelopmentData Optimization

Stack & domain

AWSSnowflakeIcebergAirflowSparkSQLEtlsData ModelingPipeline DesignCollaborationProblem SolvingData EngineeringETL

About the role

Original posting from Cloudinary via Lever

Our Data team consists of highly skilled senior software and data professionals who collaborate to solve complex data challenges. We process billions of records daily from multiple sources using multi-stage pipelines with intricate data structures and advanced queries.
We are responsible for building data pipelines end to end—from raw data ingestion to the creation of actionable datasets—following the bronze, silver, and gold paradigm. This includes business logic, infrastructure, ETLs, optimization, and ongoing maintenance.
The data we deliver drives insights and decision-making across the organization and enhances our product offerings. We leverage technologies such as AWS, Snowflake, Iceberg, Airflow, Spark, and more.
What You’ll Do
Lead the translation of business and product requirements into scalable data models, transformations, and pipelines.
Design and own datasets across bronze, silver, and gold layers, including defining grain, aggregations, and data contracts.
Develop and maintain SQL-heavy data pipelines and Airflow DAGs (workflow logic, dependencies, backfills, python, and lots of SQL).
Own data correctness for key business metrics (e.g., ARR), including deep root cause analysis and resolution of data issues.
Define and drive best practices for SQL, data modeling, and pipeline design across the team.
Optimize queries and data models for performance, scalability, and cost efficiency.
Collaborate closely with product managers, analysts, and BI developers to refine requirements and ensure high-quality data delivery.
Develop AI-agents to accelerate data analysis by internal and external users.
Work with complex data inputs (e.g., JSON, schemas, logs) and incorporate them into robust data pipelines.

Source: Cloudinary careers (Lever)