Data Analyst - Governance jobs at Jfrog in Israel, Beer Sheva

We are looking for a Data Analyst. In this role, you’ll play a vital part in ensuring the integrity, reliability, and usability of our data. You will collaborate with cross-functional teams to establish robust data governance frameworks, improve data quality, and deliver insights using SQL and Tableau. You will develop dashboards to monitor governance processes, track compliance with data policies, ensure data quality standards are met, and provide transparency to stakeholders.

• Lead data quality initiatives : Develop and implement processes to monitor, manage, and improve data quality and data curation across the organization.
• ​​ Monitor data quality: Continuously track data accuracy, consistency, and completeness to ensure high-quality data for analysis and reporting.
• Craft data governance framework : Define and enforce policies, standards, and best practices for data management and governance.
• Establish and track key data metrics : Define, measure, and report on data quality and governance KPIs.
• Collaborate with stakeholders : Partner with business units to identify data issues, gather requirements, and deliver solutions that align with business goals.
• Utilize SQL for analysis and reporting : Write and optimize complex SQL queries to extract, transform, and analyze data from multiple sources.

• 2+ years of hands-on experience in the data analysis domain
• Experience in data quality and data governance roles - advantage
• Experience with Tableau for data visualization
• Experience developing and managing data workflows in dbt Cloud, including writing SQL models and implementing best practices for modular secured and private pipelines - Must
• Excellent analytical skills and a detail-oriented approach to problem-solving.
• Ability to collaborate effectively with diverse teams and communicate technical concepts clearly to non-technical stakeholders.
• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or a related field (or equivalent work experience).

As a

• Lead the design and development of JFrog’s petabyte-scale Lakehouse and modern data platform, drive architectural decisions, and provide technical leadership to ensure it meets scalability, performance, privacy, and security requirements.
• Collaborate closely with top-notch engineers in implementation efforts to ensure alignment with architectural vision, tackle tough problems, and deliver creative solutions.
• Provide hands-on expertise through platform development and conduct architecture proof-of-concepts to validate and recommend tools, technologies, and design decisions.
• Promote the adoption and utilization of the data platform by collaborating with stakeholders to identify impactful use cases, developing enablement resources, and ensuring the platform delivers measurable business value.
• Evaluate and recommend tools and technologies to support & proliferate Data & AI-driven decision-making and make data production and consumption widespread.

• Bachelor’s or master’s in computer science, Data Science, Machine Learning, or a related field, or equivalent industry experience, is required.
• 8+ years of experience in data engineering, or a related role, preferably in large-scale, complex environments, including prior experience as a software engineer.
• Strong knowledge of big data technologies and data pipeline tools such as Kafka, Airflow, SPARK, ICEBERG, Presto and cloud-native services. Proficiency in programming languages such as Python, Java, or Scala.
• Demonstrated success in leading major data initiatives, including building data architectures from the ground up.
• Strong understanding of the intersection between software and data engineering, with experience in designing systems to meet complex and evolving data requirements.
• Excellent communication, presentation, and stakeholder engagement skills, with the ability to work cross-functionally, convey complex technical concepts, and align diverse stakeholders toward common goals.
• Comfortable operating and thriving in unexplored or ambiguous territory, with a high level of independence and self-motivation.

This role requires the experience and skills to design and build key components and infrastructure for our global data teams (Data engineering, BI, Data science) with experience in designing, building, and maintaining streaming data pipelines and data lake architectures, together with hands-on expertise with technologies like Apache Spark, Kafka, and cloud-based data lake implementations.

• Build Infrastructure to empower our Engineers/Data Scientists/BI teams to work by best practices of data processing
• Work in a high-volume production environment
• Develop and manage ETL/ELT processes for structured and unstructured data
• Collaborate with colleagues both locally and in remote locations
• Influence the software architecture and working procedures for building data and analytics
• Ensure data quality, integrity, and security within the data pipeline and data lake
• Monitor, troubleshoot, and optimize data workflows to improve performance and reliability.

• 4+ years in Data/Backend engineering with experience in designing, developing and optimizing streaming data pipelines using Apache Spark, Kafka, or similar technologies.
• Dealing with data on high volume, high availability production systems
• Practical experience with Python in the domain of data pipelines.
• Experience with cloud-based data lake architectures (AWS S3, Google Cloud Storage).
• Exposure to DevOps practices, CI/CD pipelines, and infrastructure as code.
• Excellent problem-solving skills and the ability to work in a collaborative environment.

In this high-impact role, you will spearhead the research, implementation, and operationalization of advanced AI and machine learning solutions. You will lead efforts to drive innovation by developing and implementing cutting-edge technologies in areas such as predictive analytics, NLP, and Gen AI.

As a Data Science Senior Manager in JFrog you will...

• Define and lead the strategic direction for AI and machine learning internal initiatives while collaborating closely with the CTO, marketing, sales, and customer success teams to align projects with broader business goals and deliver measurable outcomes.
• Mentor and manage a team of machine learning researchers, creating a collaborative and innovative environment that fosters technical excellence and professional growth.
• Take a hands-on approach in research and development of AI solutions, actively contributing to technical execution alongside the team.
• Leverage generative AI to develop agentic AI solutions that enhance data exploitation, content creation, customer engagement, and operational efficiency in the context of JFrog’s business goals.
• Research and operationalize machine learning models for prediction, recommendation, and optimization, driving customer behavior forecasts, sales pipeline improvements, and marketing efficiency across the B2B sales lifecycle.
• Apply data science techniques to analyze and interpret complex datasets, extracting actionable insights to support data-driven decision-making in JFrog’s B2B SaaS offering

To be a Data Science Senior Manager in JFrog you need...

• A Master’s in Computer Science, Data Science, Machine Learning, or a related field, or equivalent industry experience, is required.
• Extensive experience in machine learning, NLP, generative AI, and statistical modeling, with a demonstrated ability to develop and apply AI solutions to real-world problems in a B2B SaaS environment.
• At least 5 years of Hands-on experience proficiency in Python and ML frameworks such as TensorFlow or PyTorch, along with strong research and analysis skills and the ability to contribute directly to the development and deployment of AI models.
• At least 2 years of managerial experience, with a proven ability to lead and mentor technical teams, fostering innovation and professional growth.
• A business-oriented mindset with the ability to apply AI insights to drive impact in areas such as customer engagement, marketing, and sales optimization is highly valued.
• Comfortable operating and thriving in unexplored or ambiguous territory, with a high level of independence and self-motivation.
• Excellent communication, presentation, and stakeholder engagement skills, with the ability to work cross-functionally, convey complex technical concepts, and align diverse stakeholders toward common goals.