Principal Engineer I - Data Engg & AI

Anblicks; Dallas (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

Anblicks in Dallas is seeking an experienced data engineer to lead the design, development, and optimization of scalable data pipelines using Snowflake and dbt. You will own end-to-end data solutions, from requirements analysis and data modeling through development, testing, and production deployment.

In this role, you will craft efficient data models and ELT/CDC workflows, push for robust data quality and monitoring, and drive engineering best practices.

Qualifications

• Lead the design and maintenance of scalable data pipelines using Snowflake and dbt.
• Design efficient data models and transformation frameworks for analytics and business use.
• Develop and optimize complex SQL transformations, incremental processing, CDC, and ELT workflows.
• Establish engineering best practices around code quality, modularity, performance, and cost efficiency.

Responsibilities

• Lead design, development, optimization, and maintenance of scalable data pipelines using Snowflake and dbt.
• Own data engineering solutions end-to-end from requirements to production deployment.
• Collaborate with architects and stakeholders to translate business needs into scalable technical solutions.
• Lead technical design reviews, mentor engineers, and ensure high-quality deliverables.

Skills

Snowflake

dbt

SQL

Python

Data Modeling

ETL/ELT

CDC

Azure data services

CI/CD

Snowpark

Tools

Git

CI/CD pipelines

Deployment automation

Job description

• - Lead the design, development, optimization, and maintenance of scalable data pipelines using Snowflake and dbt.
• - Own data engineering solutions end-to-end, from requirements analysis and data modeling through development, testing, and production deployment.
• - Design efficient data models and transformation frameworks supporting enterprise analytics and business consumption.
• - Develop and optimize complex SQL transformations, incremental processing, CDC, and ELT workflows.
• - Troubleshoot complex data issues, perform root cause analysis, and implement sustainable engineering solutions.
• - Establish engineering best practices around code quality, modularity, reusability, performance optimization, and cost efficiency.
• - Build robust data quality, reconciliation, monitoring, and validation frameworks.
• - Collaborate with architects, business stakeholders, and engineering teams to translate business requirements into scalable technical solutions.
• - Lead technical design reviews, mentor engineers, and ensure high-quality deliverables.
• - Identify opportunities for automation, simplification, and continuous improvement.

Required Technical Skills

• - Snowflake: Strong hands-on expertise in Snowflake architecture, performance tuning, query optimization, warehouse sizing, Snowpark, and data loading strategies.
• - dbt: Advanced experience with dbt models, incremental strategies, macros, Jinja, testing, snapshots, documentation, and CI/CD integration.
• - SQL: Expert-level SQL skills, including complex joins, window functions, query optimization, and troubleshooting.
• - Python: Strong programming skills for data engineering, automation, and integration.
• - Data Modeling: Experience with dimensional modeling, medallion architecture, data warehousing, and enterprise data models.
• - Data Engineering: Strong understanding of ETL/ELT, batch and incremental processing, CDC, data quality, and reconciliation.
• - Cloud Platforms: Experience with Azure data services.
• - DevOps: Experience with Git, CI/CD pipelines, deployment automation, and engineering standards.