Remote Senior Data Engineer - Ingestion & Analytics
Power Digital Marketing
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Job summary
AgileEngine is seeking a Senior/Lead Data Engineer to build and maintain the pipelines and data models behind a centralized HR data warehouse. Working with Snowflake, DBT, Python, and Airflow, you will design semantic layers that make HR data consumable by BI tools and AI agents.
Experience with Snowflake Cortex or MCP-based tooling for agentic querying is a strong plus. You will handle large-scale data securely, perform real-time processing, and craft highly optimized SQL while collaborating
Qualifications
- 4+ years of experience in data engineering or related roles.
- Snowflake data modeling, datamarts, and data warehouse design.
- DBT for data transformations.
- Python programming including OOP and data scripting.
- Airflow for pipeline orchestration.
- REST API integration and data ingestion.
- Google BigQuery querying and optimization.
- Secure handling of large-scale and sensitive data.
- Real-time data processing from sources like Google Sheets or APIs.
- Strong, highly optimized SQL.
Responsibilities
- Develop and maintain secure data pipelines using DBT, PySpark, and Python.
- Build infrastructure for ETL from diverse sources using Python, DBT, Terraform, and AWS (Glue, EMR, S3).
- Monitor pipelines to maintain high uptime (target 99.5%) and maintain data models for partner teams.
- Design semantic views and ontology layers on top of dbt models to make HR data consumable by BI tools and AI agents.
- Develop and deploy AI agents (Snowflake Cortex Analyst/Search) for HR use cases enabling natural-language querying over HR data.
- Configure MCP connections between Snowflake and internal AI tooling to securely expose data to conversational and agentic interfaces.
Skills
Tools
Job description
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
We are looking for a Senior/Lead Data Engineer to build and maintain the pipelines and data models behind a centralized HR data warehouse. Working in Snowflake, DBT, Python, and Airflow, this person designs semantic layers that make HR data consumable by both BI tools and AI agents. Experience with Snowflake Cortex or MCP-based tooling for agentic querying is a strong plus.
- 4+ years of experience.
- Snowflake , including data modeling, datamarts, and data warehouse design.
- DBT for data transformations.
- Python , including object-oriented programming and data scripting.
- Airflow for pipeline orchestration.
- REST API integration and data ingestion.
- Google BigQuery querying and optimization.
- Secure handling of large-scale and sensitive data.
- Real-time data processing (e.g., from Google Sheets or APIs).
- Strong SQL , including highly optimized queries.
- Semantic layer / semantic modeling design, providing business-object abstraction over dbt and warehouse models.
- Snowflake Cortex (Cortex Analyst, Cortex Search) or equivalent LLM-native query layers.
- MCP (Model Context Protocol) or similar tool-calling / context-exposure frameworks.
- Familiarity with prompt and context engineering for grounding LLM agents in certified data sources.
- Develop and maintain secure, efficient data pipelines using DBT, PySpark, and Python applications within a supported cloud environment for HR data sources.
- Build the infrastructure and tooling required for optimal extraction, transformation, and loading of data from a wide variety of sources using Python, DBT, Terraform, and AWS technologies such as Glue, EMR, and S3.
- Identify and implement internal process improvements, develop tests within the Data Quality Framework, monitor pipelines to maintain 99.5% uptime, and create and maintain the data models used by partner teams.
- Design and build semantic views and ontology layers on top of existing dbt models (CORE → SEMANTIC → METRICS) so HR data is consumable by both BI tools and AI agents/LLMs, defining business-friendly entities, relationships, and metrics that abstract away raw warehouse structure.
- Develop and deploy AI agents (e.g., via Snowflake Cortex Analyst/Cortex Search) for HR COE use cases — including PE, iCIMS, LMS, and Sales/CS Worker agents — enabling natural-language querying over certified HRDM data.
- Configure and maintain MCP (Model Context Protocol) connections between Snowflake and internal AI tooling to securely expose HR data to conversational and agentic interfaces.
- Professional growth : Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation : USD-based pay with education, fitness, and team activity budgets.
- Exciting projects : Modern solutions with Fortune 500 and top product companies.
- Flextime : Flexible schedule with remote and office options.
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
We are looking for a Senior/Lead Data Engineer to build and maintain the pipelines and data models behind a centralized HR data warehouse. Working in Snowflake, DBT, Python, and Airflow, this person designs semantic layers that make HR data consumable by both BI tools and AI agents. Experience with Snowflake Cortex or MCP-based tooling for agentic querying is a strong plus.
- 4+ years of experience.
- Snowflake , including data modeling, datamarts, and data warehouse design.
- DBT for data transformations.
- Python , including object-oriented programming and data scripting.
- Airflow for pipeline orchestration.
- REST API integration and data ingestion.
- Google BigQuery querying and optimization.
- Secure handling of large-scale and sensitive data.
- Real-time data processing (e.g., from Google Sheets or APIs).
- Strong SQL , including highly optimized queries.
- Comprehensive documentation skills.
- Upper-intermediate English level.
- Semantic layer / semantic modeling design, providing business-object abstraction over dbt and warehouse models.
- Snowflake Cortex (Cortex Analyst, Cortex Search) or equivalent LLM-native query layers.
- MCP (Model Context Protocol) or similar tool-calling / context-exposure frameworks.
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