Since 2012 Odaseva has helped global enterprises protect and secure their most valuable asset: data.
Our platform and tools empower data-driven organizations to combat evolving threats, maintain operational integrity, and comply with data regulations.
Our products include Backup and Restore, Archiving, Data Privacy solutions and much more.
We’re a fast-growing scale-up with offices in San Francisco, Paris, Sydney, London, Kuala Lumpur, Singapore, and more.
We serve a global customer base including Fortune 500 companies, government organizations, and NGOs, reaching more than 100 million Salesforce users worldwide.
At Odaseva, our values — Trust, Service, Commitment, Excellence, Kaizen, and One Team — define the environment we foster for our employees to thrive and succeed.
Due to significant growth and to address the needs of our Product, we are seeking a Data Solutions Engineer.
This role is a unique blend of data engineering and data analysis, requiring both technical expertise and strong business acumen.
You will be responsible for the development and maintenance of Odaseva's analytics and AI platform, ensuring data accuracy and scalability.
You will also play a key role in delivering customer-facing analytics features and providing data-driven insights to guide product strategy and optimize investments.
This role requires a strong understanding of data engineering principles, data analysis techniques, and product management methodologies.
Key Responsibilities:
- Analytics & AI Platform Ownership: Own the development and maintenance of Odaseva's analytics & AI tools, ensuring data accuracy, reliability, and scalability. Continuously enhance the platform to support evolving business needs and provide a robust foundation for data-driven insights. This includes aspects of data engineering like building and maintaining data pipelines, ensuring data quality, and optimizing data infrastructure.
- Customer-facing analytics: Develop with the product team to build and deliver insightful product analytics features to our customers, empowering them to make informed decisions based on their own data.
- Product metrics expertise: Become the authority on product usage, sales, and customer behavior data. Deeply understand key performance indicators (KPIs), identify trends and patterns, and provide actionable insights to guide product strategy and roadmap planning.
- Adoption & investment optimization: Utilize data analysis to identify opportunities for enhancing product adoption and engagement. Provide strategic guidance to prioritize investments and ensure resources are allocated effectively to drive maximum impact.
- Data-driven storytelling: Translate complex data into clear and compelling narratives, using visualizations and presentations to communicate findings and recommendations to both technical and non-technical audiences.
- Cross-functional collaboration: Work closely with product management, engineering, marketing, and sales teams to gather requirements, understand business objectives, and ensure alignment on data-driven initiatives.
Skills and Qualifications:
- Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, or a related field.
- 7+ years of experience in a data analysis role, preferably within a product or tech environment.
- Proven track record of owning and enhancing analytics platforms.
- Advanced SQL skills for querying and optimizing large datasets.
- Proficiency in data visualization tools (e.g., Salesforce CRM Analytics, Tableau, Looker).
- Experience with statistical analysis and machine learning techniques.
- Data Pipelines: Experience with data pipeline tools (e.g., Apache Airflow, dbt) for automating data workflows.
- Cloud Data Warehousing: Familiarity with cloud-based data warehousing solutions (e.g., Snowflake, BigQuery, Redshift) for scalable and efficient data storage.
- Data Modeling: Knowledge of data modeling techniques (e.g., dimensional modeling, star schema) for designing effective data structures.
- Scripting: Experience with scripting languages for data processing (e.g., Python, R).
- Data Governance: Understanding of data governance and security best practices.
- Statistical Analysis: Experience with statistical analysis methods for extracting insights from data.
- Machine Learning: Familiarity with machine learning techniques for predictive modeling and data mining.
- Experience in delivering data products or reports to external clients.
- Familiarity with product management frameworks and agile methodologies is a plus.
- Experience with Salesforce and CRM Analytics is highly desirable.
- Strong problem-solving skills and attention to detail.
- Excellent communication and presentation skills, with the ability to translate complex data into actionable insights.
- Self-motivated and proactive, with a passion for data and product development.
- Ability to work effectively in a cross-functional team environment.
- Excellent communication skills to convey technical concepts to non-technical stakeholders.
Core Skills:
Data Engineering Skills:
Business Acumen & Communication:
Soft Skills:
More about Odaseva:
Odaseva is an Equal Opportunity Employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
For more informations and follow us: Linkedin and Odaseva.com
Top Skills
What We Do
At enterprise scale, Salesforce data is different. Data volumes are large. Data models are more sophisticated. Integrations, regulations, and business processes are much more intricate. All this complexity dramatically increases the risks to your data threatening to grind business to a halt. Odaseva is the only data platform built specifically to help the world's largest, most ambitious Salesforce customers keep their data protected, compliant, and agile.
With Odaseva, Salesforce architects and platform owners get a powerful set of tools to help solve the problems at the foundation of the Salesforce data value chain. Keep customer data intact and available with comprehensive backup and archiving, apply analytics to prevent disruptions before they happen, use automation to take control of the entire data lifecycle and solve privacy and compliance issues at the root, and easily move data between production and non-production environments, to sandboxes, and to systems outside Salesforce.
White Paper: Odaseva Complete Guide to Salesforce Backup and Restore
https://www.odaseva.com/complete-guide-to-salesforce-backup-and-restore