Role Overview:This role focuses on designing, developing, and maintaining robust data pipelines and data models using Snowflake and Palantir Foundry to support analytics, reporting, and AI/ML initiatives. The engineer will be responsible for ensuring high-quality, reliable data delivery and optimizing data assets for governed consumption and business insights.
Key Responsibilities:- Design, develop, and maintain scalable data ingestion, integration, transformation, and orchestration pipelines across enterprise applications, cloud platforms, data warehouses, and operational systems.
- Utilize technologies such as Snowflake, Palantir Foundry, Snowpipe, Snowpark, dbt, and related cloud-native tools to ensure trusted, high-quality, and reliable data delivery for analytics, reporting, and AI/ML initiatives.
- Build and optimize enterprise data models, data marts, ontology-driven data products, semantic layers, and reusable data assets within Snowflake and Palantir Foundry.
- Enable governed data consumption, self-service analytics, operational applications, decision intelligence, and business insights through platforms like Power BI, Tableau, and ThoughtSpot.
- Monitor, troubleshoot, and continuously improve platform performance, data quality, lineage, governance, security, operational reliability, and cost efficiency.
- Manage data pipelines, resolve ETL/ELT and data processing issues, and implement data observability and validation controls.
- Ensure compliance with enterprise data standards, governance policies, security requirements, and operational SLAs.
Required Skills:- Proficiency with Snowflake and Palantir Foundry.
- Experience with data ingestion, integration, transformation, and orchestration pipelines.
- Familiarity with Snowpipe, Snowpark, and dbt.
- Knowledge of enterprise data modeling, data marts, and semantic layers.
- Experience with analytics platforms such as Power BI, Tableau, and ThoughtSpot.
- Ability to monitor and troubleshoot platform performance, data quality, and governance issues.
Qualifications:- Effectively collaborate with business stakeholders, data architects, analysts, and cross-functional teams.
- Provide technical guidance, coordinate priorities, and ensure successful delivery of analytics initiatives.
- Drive work planning, effort estimation, risk management, and process improvement.
- Ensure adherence to governance, quality standards, and project timelines.
