Key skills
Amazon RedshiftAWSAzureBigQueryCloudDynamoDBETLJavaJavaScriptKafkaMongoDBPostgresPythonScalaSplunkSQLTableauArtificial IntelligenceMachine LearningAnthropicGeminiELTData EngineeringAnalyticsBIPower BISnowflakeRedshiftDatabricksS3KinesisPostgreSQLDatadogOtel
About this role
Role Overview
- Architect, build and maintain high-volume, high-fidelity security data modeling in Snowflake system for detection engineering and threat hunting use cases
- Lead the ingestion, normalization, enrichment, and correlation of raw security telemetry, including logs, events, metrics, alerts, config, scanning and other data types
- Define and enforce data standards, schemas, and normalization frameworks across security data sources.
- Leverage SQL, Python, PowerBI and other interfaces in Snowflake to design the right solution for data analytics, including reporting and other metrics.
- Partner with Security Operations, Threat detection, GRC and other engineering teams to translate security requirements into scalable data solutions.
- Serve as a technical authority and mentor, influencing data engineering, security analytics and platform strategy.
- Drive continuous improvement in data reliability, performance, and cost efficiency.
- Manage Data Governance with various reporting and quality checks.
- Research and look for opportunities to adopt the best practices and industry standards
- Identify opportunities to enhance the current baseline processes and configuration
- Produce engineering, integration and process related documentation.
- Manage vendor relationships to drive roadmap, solution design, implementation and troubleshooting
- Able to conduct the POC of new features to develop new solutions
Requirements
- At least 10+ years of experience in database engineering with significant focus on security data (logs, scanning, configuration, vulnerability, etc.), analytics, detection and platform engineering
- 8+ years of hands-on experience with various databases including Snowflake, relational (SQL, PostgreSQL, etc.), no-SQL (MongoDB, DynamoDB, etc.)
- At least 2+ years of experience with data warehouses and data lakes Snowflake, Databricks, BigQuery, Redshift, Azure Synapse
- At least 1+ years of experience with reporting tools such PowerBI, Tableau, etc.
- Familiarity with SIEM products such as Splunk, Cribl, Elastic, Datadog, AWS CloudTrail, cloud watch, Azure event hub, AWS S3, etc.
- Familiarity with streaming platforms like Cribl, Kafka, Kinesis, etc.
- Solid knowledge of ETL/ELT pipelines and data ingestion processes
- Strong programming skills in Python, SQL and/or Java/Scala and JavaScript
- Experience with data modeling, data normalization and schema design
- Ability to understand, clean, and transform raw data into structure, usable formats
- Experience working with large-scale datasets (batch and streaming)
- Experience in analyzing raw data and performing data normalization.
- Implementing data validation, quality checks and error handling
- Understanding of data governance and metadata management
- Strong problem-solving and analytical skills
- Must have working knowledge of Artificial Intelligence and Machine Learning technologies. Anthropic, ChatGPT, Gemini, Co-Pilot, etc.
- Experience with real-time analytics
- Familiarity with BI tools (Power BI, Tableau)
- Knowledge of data privacy, compliance and security best practices
- Familiar with data standards such as OCSF, OTEL, etc.
- Familiar with industry security regulations and frameworks (MITRE Attack Framework, CRI, etc.)
- Experience with at least one major cloud provider AWS, Azure or Google
Tech Stack
- Amazon Redshift
- AWS
- Azure
- BigQuery
- Cloud
- DynamoDB
- ETL
- Java
- JavaScript
- Kafka
- MongoDB
- Postgres
- Python
- Scala
- Splunk
- SQL
- Tableau
Benefits
- comprehensive health and wellness benefits
- retirement plans
- educational assistance and training programs
- income replacement for qualified employees with disabilities
- paid maternity and parental bonding leave
- paid vacation, sick days, and holidays