The Role
Design, build, and maintain ETL/ELT pipelines and lakehouse architectures. Write and optimize SQL in Snowflake, support cloud integrations (AWS, Lambda), enforce data governance, monitor pipelines, troubleshoot data quality, and document processes while collaborating with BI and analytics teams.
Summary Generated by Built In
Saviynt's AI-powered identity platform manages and governs human and non-human access to all of
an organization's applications, data, and business processes. Customers trust Saviynt to safeguard
their digital assets, drive operational efficiency, and reduce compliance costs. Built for the AI age,
Saviynt is today helping organizations safely accelerate their deployment and usage of AI. Saviynt is
recognized as the leader in identity security, with solutions that protect and empower the world’s
leading brands, Fortune 500 companies and government institutions. For more information, please
visit www.saviynt.com.
We are seeking a motivated Sr. Data Engineer with 5-8 years of experience in snowflake to join our growing data team. This role is ideal for candidates eager to build a career in data engineering, working closely with Business, analysts, and BI developers. You will contribute to designing, building, and maintaining data pipelines and infrastructure that ensure reliable, high-quality data for business decision-making.
WHAT YOU WILL BE DOING
- Develop, test, and maintain ETL/ELT pipelines for data ingestion and transformation.
- Assist in designing and implementing data models, database schemas, and lakehouse architectures.
- Write and optimize SQL queries in Snowflake for data extraction and
- reporting.
- Collaborate with BI developers and analysts to ensure data accessibility and usability.
- Monitor and troubleshoot data workflows to maintain system reliability.
- Support migration and integration projects involving cloud platforms (e.g., AWS Lambda) and Python.
- Expert level knowledge of Python Scripting.
- Document processes, pipelines, and best practices for knowledge sharing.
- Apply AI agents for data modeling and quality assurance.
- Manage user permissions and security roles to ensure data governance and compliance.
- Monitor database performance and recommend improvements.
- Troubleshoot data integration issues and resolve data quality discrepancies.
WHAT YOU BRING
- Bachelor’s degree in computer science, Information Systems, Business Analytics, Data Science, or related field (or equivalent experience).
- Up to 5 years of experience in data engineering with a strong background in SQL development.
- Expert Level knowledge in snowflake.
- Strong experience with SQL and scripting (queries, stored procedures, functions).
- Exposure of fivetran tool (good to have)
- Experience in data warehousing and data modeling concepts.
- Familiarity with agentic AI for data engineering tasks
- Certifications in relevant tools (e.g., SQL or Snowflake, Azure).
- Exposure to reporting tools (e.g., Tableau – good to have).
- Experience with cloud-based BI solutions (AWS).
- Familiarity with Agile development methodologies.
- Basic knowledge of ERP tools (e.g., Salesforce).
- Knowledge of data governance, privacy, and security best practices.
- Soft Skills
- Strong analytical and problem-solving abilities.
- Excellent communication skills for both technical and non-technical stakeholders.
- Ability to work independently and collaboratively in a team environment.
- Attention to detail and commitment to quality.
Skills Required
- Bachelor's degree in Computer Science, Information Systems, Business Analytics, Data Science, or related field (or equivalent experience).
- 3-5 years of experience in data engineering with strong SQL development.
- Expert-level Python scripting.
- Strong experience with SQL and Snowflake (queries, stored procedures, functions).
- Experience in data warehousing and data modeling concepts.
- Experience developing, testing, and maintaining ETL/ELT pipelines and lakehouse architectures.
- Experience with cloud platforms and cloud-based BI solutions (AWS, including AWS Lambda).
- Knowledge of data governance, privacy, and security best practices; manage user permissions and security roles.
- Certifications in relevant tools (e.g., SQL, Snowflake, Azure).
- Familiarity with Agile development methodologies.
- Familiarity with agentic AI for data engineering tasks.
- Basic knowledge of ERP tools (e.g., Salesforce).
- Exposure to Fivetran (good to have).
- Exposure to reporting tools (e.g., Tableau) (good to have).
- IGA tool knowledge (good to have).
Saviynt Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Saviynt and has not been reviewed or approved by Saviynt.
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Leave & Time Off Breadth — Time off is described as flexible, with policies including flexible time off and mentions of unlimited PTO. This breadth can make time away easier to take alongside company holidays.
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Wellbeing & Lifestyle Benefits — In‑office amenities such as catered food, drinks, and snacks, plus social events like birthday celebrations and team outings, are highlighted. These lifestyle perks add day‑to‑day convenience and connection.
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Career-Linked Recognition & Rewards — Employee recognition is emphasized, with programs to celebrate those who go above and beyond. Regular recognition activities are cited alongside team bonding initiatives.
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The Company
What We Do
Saviynt’s Enterprise Identity Cloud helps modern enterprises scale cloud initiatives and solve the toughest security and compliance challenges in record time. The company brings together identity governance (IGA), granular application access, cloud security, and privileged access to secure the entire business ecosystem and provide a frictionless user experience.
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