Data Engineer - Snowflake
About the role
We are looking for a Snowflake Data Engineer with strong administration and engineering experience to manage, optimize, and support enterprise data platforms.
Responsibilities
- Manage and administer Snowflake environments, including user roles, access control, and security policies.
- Configure and maintain warehouses, databases, schemas, and resource monitors.
- Maintain system performance, query usage, and cost optimization.
- Implement data security, encryption, masking policies, and governance controls.
- Handle Snowflake account setup, backup, and disaster recovery strategies.
- Design and build scalable data pipelines using Snowflake and Databricks (PySpark/SQL).
- Develop and maintain ETL/ELT pipelines for structured and semi-structured data.
- Optimize SQL queries and perform performance tuning for large datasets.
- Support data ingestion via Snowpipe, Tasks, Streams, and external stages.
- Work with business stakeholders to gather data requirements and define technical solutions.
- Translate business needs into scalable data models and pipelines.
- Participate in solution design discussions and architecture planning.
- Contribute to the design of data warehouse and lakehouse architecture.
- Develop logical/physical data models and ensure alignment with best practices.
- Ensure high availability, scalability, and performance of the data platform.
Requirements
- Strong experience in Snowflake Administration
- Hands-on experience with Databricks / Spark / PySpark
- Advanced SQL (query optimization and tuning)
- Python / PySpark ETL/ELT pipeline development
- Experience with AWS / Azure / GCP
- Knowledge of cloud storage (S3, ADLS, etc.)
- Data warehousing and modeling (Star/Snowflake schema)
- Performance tuning and optimization
- Data governance and security best practices
- Experience with orchestration tools such as Airflow / Azure Data Factory
- Familiarity with Delta Lake / Lakehouse architecture
- Exposure to CI/CD tools and Git
- Knowledge of monitoring and alerting frameworks
Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
Skills
- Strong experience in Snowflake Administration
- Hands-on experience with Databricks / Spark / PySpark
- Advanced SQL (query optimization and tuning)
- Python / PySpark ETL/ELT pipeline development
- Experience with AWS / Azure / GCP
- Knowledge of cloud storage (S3, ADLS, etc.)
- Data warehousing and modeling (Star/Snowflake schema)
- Performance tuning and optimization
- Data governance and security best practices
- Experience with orchestration tools such as Airflow / Azure Data Factory
- Familiarity with Delta Lake / Lakehouse architecture
- Exposure to CI/CD tools and Git
- Knowledge of monitoring and alerting frameworks
Benefits
The base compensation range for this role in the posted location is: $112,700 - $148,000. Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Pay
The base compensation range for this role in the posted location is: $112,700 - $148,000.
Schedule
N/A