- Salary
- $140k – $160k
- Location
- Dallas, United States
- Department
- Engineering
- Seniority
- Lead
- Source
- Keka
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.
Skills
PythonAzureCI/CDSQLSnowflakeData EngineeringETLGitDevOps