Senior Data Engineer

Gardner Resources Consulting, LLC; Dallas (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

A consulting firm in the United States is seeking a Senior Data Engineer with over 10 years of experience to drive scalable data solutions. This role involves designing data pipelines, leveraging Snowflake and dbt, and collaborating with cross-functional teams to enable advanced analytics and AI/ML projects. Ideal candidates are proficient in cloud environments and are effective communicators. This position offers an excellent opportunity to mentor junior staff and shape data strategy within an innovative team.

Qualifications

• 10+ years of experience in data engineering with strong expertise in modern data platforms.
• Proficiency in snowSQL, Python, and dbt for data pipeline development.
• Experience in designing AI/ML-ready data ecosystems.

Responsibilities

• Design and optimize data pipelines across modern data platforms.
• Leverage Snowflake and cloud-native solutions for scalable data transformations.
• Collaborate with Data Scientists and Engineers for integrated data solutions.

Skills

Data warehousing

Snowflake

Python

dbt

AI/ML data ecosystems

Cloud environments (AWS, Azure, GCP)

Communication

Collaboration

Job description

We are seeking a Senior Data Engineer with 10+ years of experience to support a growing Data & Analytics team. This role will focus on building scalable, modern data solutions that enable advanced analytics and AI/ML use cases.

Key Responsibilities:

• Design, build, and optimize data pipelines and workflows across modern data platforms.
• Leverage Snowflake, cloud-native solutions, and dbt to deliver scalable data transformations.
• Develop and maintain high-quality, production-ready datasets to support AI/ML initiatives.
• Collaborate with cross-functional stakeholders, including Data Scientists and Engineers, to deliver integrated data solutions.
• Mentor junior team members and contribute to best practices in data engineering.
• Participate in architecture discussions and provide input on data strategy and platform evolution.

Must Haves:

• 10+ years of experience in data engineering, with strong expertise in data warehousing and modern data platforms (Snowflake preferred).
• Proficiency with snowSQL, Python, and dbt for building and maintaining data pipelines.
• Experience designing AI/ML-ready data ecosystems and supporting advanced analytics.
• Proven success in leading cross-functional initiatives and mentoring engineering teams.
• Strong understanding of cloud environments (AWS, Azure, or GCP).
• Excellent communication and collaboration skills.

Nice-to-Have:

• Experience with MLOps tools and practices.
• Familiarity with data governance and security best practices.
• Background in healthcare, CPG, or regulated industries.