Sr. Snowflake Engineer

Job Description :

• Architect, develop, and maintain scalable high-volume security data platforms on Snowflake to support SIEM, SOAR, UEBA, ETL pipelines, and detection engineering initiatives.
• Lead ingestion, normalization, enrichment, and correlation of diverse security telemetry including logs, alerts, metrics, events, configurations, and vulnerability scan data using Snowflake technologies such as Cortex and Grid.
• Establish and enforce enterprise-wide security data standards, schemas, and normalization frameworks across multiple data sources.
• Design advanced analytics, dashboards, and reporting solutions using SQL, Python, Power BI, and Snowflake-native capabilities.
• Collaborate with Security Operations, Threat Detection, GRC, and engineering teams to translate business and security requirements into scalable data solutions.
• Act as a technical leader and mentor for data engineering and security analytics initiatives, contributing to platform strategy and best practices.
• Drive continuous improvements in platform reliability, performance optimization, scalability, and cost efficiency.
• Implement and manage data governance, quality assurance, compliance reporting, and operational monitoring processes.
• Research emerging technologies, evaluate industry best practices, and conduct POCs to introduce innovative security data solutions and enhancements.
• Produce technical documentation, support vendor management activities, and oversee solution design, implementation, troubleshooting, and process optimization.

• 10+ years of experience in Data Engineering with strong expertise in security analytics, detection engineering, and platform engineering.
• Extensive hands-on experience with relational and NoSQL databases including SQL Server, PostgreSQL, MongoDB, and DynamoDB.
• Proven experience working with modern data warehouses and data lake technologies such as Snowflake, Databricks, BigQuery, Redshift, and Azure Synapse.
• Strong knowledge of ETL/ELT pipelines, large-scale data ingestion, transformation, normalization, and schema design for both batch and streaming datasets.
• Proficient in Python, SQL, Java, and JavaScript for data engineering, automation, analytics, and integration development.
• Experience with SIEM, observability, and streaming platforms including Splunk, Cribl, Elastic, Datadog, Kafka, Kinesis, AWS CloudTrail, CloudWatch, Azure Event Hub, and AWS S3.
• Skilled in implementing data governance, metadata management, data quality validation, error handling, and compliance-focused data security practices.
• Hands-on experience with BI and reporting tools such as Power BI and Tableau, including real-time analytics and dashboard development.
• Strong understanding of AI/ML technologies and modern AI platforms including Anthropic, ChatGPT, Gemini, and GitHub Copilot.
• Familiarity with cloud platforms (AWS, Azure, or GCP), security standards such as OCSF and OTEL, and frameworks including MITRE ATT&CK and other cybersecurity best practices.