Remote Senior Data Engineer - Data Ingestion & Integrations
Pyyne Digital
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Benefits offered by this job
Job summary
AgileEngine is seeking a Senior/Lead Data Engineer to build and maintain pipelines for a centralized HR data warehouse. You will work with Snowflake, DBT, Python, and Airflow, designing semantic layers for BI tools and AI agents. Experience with Cortex or MCP-based tooling is a plus.
Join a people-first team with flexible remote/office options and an award-winning culture. 4+ years of relevant experience and strong SQL are required.
Qualifications
- 4+ years of experience.
- Snowflake, including data modeling, datamarts, and data warehouse design.
- DBT for data transformations.
- Python, including OO 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 Sheets or APIs).
- Strong SQL, including highly optimized queries.
- Comprehensive documentation skills.
- Upper-intermediate English level.
Responsibilities
- Develop and maintain secure, efficient data pipelines using DBT, PySpark, and Python applications.
- Build infrastructure and tooling required for optimal extraction, transformation, and loading using Python, DBT, Terraform, and AWS (Glue, EMR, S3).
- Identify and implement internal process improvements, develop tests within the Data Quality Framework, monitor pipelines to maintain uptime, and maintain data models.
- Design and build semantic views and ontology layers on top of existing dbt models to make HR data consumable by BI tools and AI agents.
- Develop and deploy AI agents for HR use cases enabling natural-language querying over certified HR data.
- Configure and maintain MCP connections between Snowflake and internal AI tooling.
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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