Senior Snowflake Data Engineer

Job Description

We are seeking a Senior Snowflake Data Engineer with strong hands-on experience in Snowflake and Databricks to join our data engineering team in Dallas, TX. The ideal candidate will be responsible for designing, developing, and optimizing scalable data pipelines and data solutions supporting enterprise analytics and business intelligence initiatives.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Snowflake and Databricks.
• Develop complex data transformations using SQL, Python, and PySpark.
• Build and optimize data pipelines using Databricks, Delta Lake, and Spark.
• Design and implement data models, data warehouses, and data marts within Snowflake.
• Develop and maintain batch and real-time data ingestion pipelines.
• Optimize Snowflake queries, warehouses, tables, and overall performance.
• Implement data quality, validation, monitoring, and error-handling processes.
• Work with cloud-based data platforms and integrate data from multiple enterprise sources.
• Collaborate with data architects, analysts, developers, and business stakeholders to understand requirements and deliver scalable solutions.
• Implement best practices around data security, governance, access control, and performance optimization.
• Participate in code reviews, technical design discussions, and production support.
• Troubleshoot data pipeline and performance issues and provide root-cause analysis.
• Contribute to CI/CD and automation practices for data engineering workflows.

Required Skills

• 7+ years of experience in Data Engineering.
• Strong hands-on experience with Snowflake and enterprise data warehousing.
• Strong experience with Databricks, Apache Spark, and PySpark.
• Advanced SQL skills, including complex queries, CTEs, window functions, and performance tuning.
• Strong Python programming experience.
• Experience building robust ETL/ELT pipelines.
• Experience with Delta Lake and modern lakehouse architecture.
• Experience with data modeling, dimensional modeling, and data warehouse concepts.
• Experience working with large-scale datasets and distributed processing.
• Strong understanding of data engineering best practices and SDLC.
• Experience with Git and CI/CD tools.

Preferred Skills

• Experience with AWS, Azure, or Google Cloud Platform cloud environments.
• Experience with Snowflake Snowpipe, Streams, Tasks, and Dynamic Tables.
• Experience with Databricks Workflows, Unity Catalog, and Delta Live Tables/Lakeflow.
• Experience with Apache Airflow or other workflow orchestration tools.
• Familiarity with Kafka or other streaming technologies.
• Experience with data governance and security frameworks.
• Experience working in Agile/Scrum environments.
• Prior experience in the financial services, payroll, HR, or fintech domain is a plus.

Ideal Candidate

The ideal candidate is a senior-level data engineer who can work across both Snowflake data warehousing and Databricks lakehouse technologies, is highly proficient in SQL/Python/PySpark, and can independently design and deliver production-grade data solutions.