Sr. Data Engineer (Snowflake/dbt)

Teamsparq; Snowflake (AZ); Remote; USD 90,000 - 150,000; Full time

Job summary

An established industry player is seeking a Senior Data Engineer to join their innovative team. In this role, you will work with cutting-edge cloud data technologies, tackling enterprise-scale data challenges while collaborating with diverse teams. Your expertise in Snowflake and dbt will be essential as you design and build scalable data pipelines, optimize performance, and lead efforts to refine legacy processes. With a focus on mentorship and professional growth, this fully remote position offers a dynamic environment where your contributions will significantly impact the company's digital transformation journey. If you are passionate about data engineering and eager to make a difference, this opportunity is perfect for you.

Qualifications

• 3+ years of experience in data engineering focusing on cloud-based solutions.
• Hands-on expertise in Snowflake performance tuning and dbt for data transformation.

Responsibilities

• Design and build scalable data pipelines in Snowflake and dbt.
• Optimize Snowflake storage and compute performance for efficiency.
• Lead migration and refinement of legacy data processes in Snowflake.

Skills

Data Engineering

Snowflake Optimization

SQL

Python

Data Governance

Problem-Solving

Communication Skills

Tools

dbt

Airflow

AWS

GCP

Azure

Job description

Team Sparq is committed to creating high-quality tech careers while helping clients accelerate their digital transformation journey. We are committed to being an inclusive workplace, maintaining a culture of equitable, diverse employment and advancement company-wide.

Why You’ll Love This Role:

• Work with cutting-edge cloud data technologies in a dynamic, collaborative environment
• Tackle enterprise-scale data challenges, working with billions of rows of data
• Opportunities for career growth and skill development through mentorship and certification programs
• Fully remote work flexibility

About the Role:

We are seeking a Senior Data Engineer with expertise in Snowflake and dbt, with a strong focus on scalability and optimization. The ideal candidate has experience working with massive datasets at the enterprise level and can fine-tune and optimize Snowflake environments to enhance performance, cost efficiency, and best practices.

Responsibilities:

• Design and build scalable data pipelines in Snowflake and dbt, ensuring they can handle billions of rows of data efficiently
• Optimize Snowflake storage, compute performance, and query execution to improve processing speed and cost efficiency
• Lead efforts in migrating and refining legacy data processes in Snowflake using dbt, ensuring optimized transformations and modeling
• Collaborate with business and data teams to understand requirements and translate them into high-performance data solutions
• Implement best practices for Snowflake optimization, including clustering, partitioning, indexing, materialized views, and workload management
• Troubleshoot and resolve bottlenecks in existing Snowflake-based ETL/ELT workflows
• Provide technical leadership and mentorship, ensuring the team follows best practices for scalable data engineering
• Create and maintain technical documentation, including architecture diagrams and optimization guidelines

What You Bring:

• 3+ years of experience in data engineering, with a focus on cloud-based enterprise-scale data solutions
• Proven experience working with massive datasets (billions of rows) in Snowflake
• Hands-on expertise in Snowflake performance tuning, storage optimization, and cost management
• Deep experience with dbt for data transformation, testing, and workflow orchestration
• Strong proficiency in SQL and Python for data manipulation, automation, and optimization
• Ability to identify, diagnose, and optimize inefficient queries and processing workflows
• Experience working both with and without an architect to optimize Snowflake performance
• Strong understanding of data governance, security best practices, and role-based access control in Snowflake
• Excellent problem-solving and communication skills, with the ability to collaborate across teams

Bonus Points for:

• Experience with orchestration tools like Airflow or Prefect
• Exposure to AWS, GCP, or Azure for cloud data integration
• Familiarity with streaming data pipelines (Kafka, Kinesis, etc.)

Equal Employment Opportunity Policy: Sparq is proud to offer equal employment opportunity without regard to age, color, disability, gender, gender identity, genetic information, marital status, military status, national origin, race, religion, sexual orientation, veteran status, or any other legally protected characteristic.