Data Engineer

Tel Aviv-Yafo - إسرائيل

الراتب شهرياً: لم يكشف

تاريخ النشر: نُشرت قبل 2 ساعة

عدد الوظائف الشاغرة: 1 عدد الوظائف الشاغرة

سجل للتقديم

ملخص الوظيفة

We are looking for an Experienced Data Engineer to take end-to-end ownership of our data platform and production data this role you will be responsible for building robust scalable and observable data systems that power analytics reporting and downstream business use cases. You will work deeply hands-on with data infrastructure modeling and orchestration and act as a key technical partner to Marketing Sales Product and Business and Finance teams.

This role suits someone who enjoys working close to the metal designing systems that scale and solving ambiguous data problems in a dynamic startup environment. You will play a critical role in shaping how data flows through the company setting engineering standards and ensuring data is trustworthy performant and ready for growth.

About The Role:

What Youll Do:

Design build and maintain scalable reliable data pipelines and data warehouse architectures to support analytics and business intelligence needs.
Own the end-to-end ETL/ELT processes ingesting data from internal and external sources transforming it and making it analytics-ready.
Model and optimize data structures (fact tables dimensions semantic layers) to support performant querying and reporting.
Ensure high standards of data quality integrity observability and reliability across all data assets.
Partner closely with Analytics Product Marketing and Finance teams to understand data requirements and deliver robust data solutions.
Implement monitoring alerting and testing frameworks to proactively identify data issues.
Optimize warehouse performance and cost efficiency (query optimization partitioning clustering etc.).
Identify gaps in data collection and work with engineering teams to improve instrumentation and data availability.
Support experimentation and analytics use cases by enabling clean trustworthy datasets for A/B testing and analysis.
Document data models pipelines and best practices to support scale and knowledge sharing.

Requirements:

Bachelors or Masters degree in Computer Science Data Engineering Software Engineering or a related technical field.
35 years of hands-on experience as a Data Engineer preferably in a SaaS or technology-driven environment.
Strong experience designing and maintaining data warehouses (e.g. Snowflake BigQuery Redshift).
Proven expertise with ETL/ELT tools and frameworks (e.g. Airflow dbt Talend SSIS Informatica or similar).
Advanced SQL skills and solid proficiency in Python (or similar languages) for data processing and orchestration.
Strong understanding of data modeling warehousing best practices and analytics engineering concepts.
Experience integrating data from business systems such as Salesforce HubSpot or other SaaS platforms.
Familiarity with SaaS metrics and business concepts (ARR churn LTV CAC) from a data modeling perspective.
Experience supporting BI tools and analytics consumers (Tableau Looker Power BI etc.).
Strong problem-solving skills attention to detail and a passion for building reliable data foundations.
Excellent communication skills and the ability to collaborate across technical and non-technical teams.

Datarails is a financial planning and analysis platform that automates financial reporting and planning while enabling finance teams to continue using Excels familiar spreadsheets and financial models.We are looking for an Experienced Data Engineer to take end-to-end ownership of our data platform a...

About The Role:

What Youll Do:

Design build and maintain scalable reliable data pipelines and data warehouse architectures to support analytics and business intelligence needs.
Own the end-to-end ETL/ELT processes ingesting data from internal and external sources transforming it and making it analytics-ready.
Model and optimize data structures (fact tables dimensions semantic layers) to support performant querying and reporting.
Ensure high standards of data quality integrity observability and reliability across all data assets.
Partner closely with Analytics Product Marketing and Finance teams to understand data requirements and deliver robust data solutions.
Implement monitoring alerting and testing frameworks to proactively identify data issues.
Optimize warehouse performance and cost efficiency (query optimization partitioning clustering etc.).
Identify gaps in data collection and work with engineering teams to improve instrumentation and data availability.
Support experimentation and analytics use cases by enabling clean trustworthy datasets for A/B testing and analysis.
Document data models pipelines and best practices to support scale and knowledge sharing.

Requirements:

Bachelors or Masters degree in Computer Science Data Engineering Software Engineering or a related technical field.
35 years of hands-on experience as a Data Engineer preferably in a SaaS or technology-driven environment.
Strong experience designing and maintaining data warehouses (e.g. Snowflake BigQuery Redshift).
Proven expertise with ETL/ELT tools and frameworks (e.g. Airflow dbt Talend SSIS Informatica or similar).
Advanced SQL skills and solid proficiency in Python (or similar languages) for data processing and orchestration.
Strong understanding of data modeling warehousing best practices and analytics engineering concepts.
Experience integrating data from business systems such as Salesforce HubSpot or other SaaS platforms.
Familiarity with SaaS metrics and business concepts (ARR churn LTV CAC) from a data modeling perspective.
Experience supporting BI tools and analytics consumers (Tableau Looker Power BI etc.).
Strong problem-solving skills attention to detail and a passion for building reliable data foundations.
Excellent communication skills and the ability to collaborate across technical and non-technical teams.

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