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Sparq

Sr. Data Engineer (Snowflake/dbt)

Posted 13 Days Ago
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Remote
Hiring Remotely in Chile
Senior level
Remote
Hiring Remotely in Chile
Senior level
Senior Data Engineer responsible for designing and optimizing scalable Snowflake and dbt pipelines to handle billions of rows. Improve performance, storage, query execution, and cost efficiency; migrate/refine legacy processes; troubleshoot bottlenecks; provide technical leadership, mentorship, and documentation.
The summary above was generated by AI

At Sparq, we help companies solve the right problems—not just build more technology.


We’re a modern product engineering partner blending strategy, craftsmanship, and speed to help organizations modernize confidently in the age of AI. From data ecosystems to digital products and AI acceleration, we turn complexity into clarity and ideas into impact.


If you’re driven to build what’s next, lead with empathy, and deliver excellence without ego, you’ll feel right at home at Sparq.


Why you will enjoy Mondays again:

  • Opportunity to work alongside a talented, diverse team in a collaborative and creative environment
  • Ongoing investment in your growth through training, mentorship, and industry certifications
  • Hands-on exposure to cutting-edge technologies across multiple industries
  • Recognition programs and employee awards within an inclusive culture that celebrates great work, including our AI Innovators Program
  • Remote or hybrid work options

A Day in the Life:

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.

  • 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
  • Actively use AI tools, including Claude through our Anthropic partnership, to streamline tasks, improve the quality of your work, and share best practices with teammates while continuously seeking new ways to integrate AI into your everyday workflows
  • 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 it Takes:

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

Regardless of your specific role, we seek individuals who are excited to explore, adopt, and evangelize AI tools and methodologies. If you have experience in AI or a proven track record of rapidly learning and mentoring others on emerging tech, you’ll fit right in.


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.


We are committed to providing equal employment opportunities and believe in an inclusive workplace. If you require reasonable accommodations to participate in the job application or interview process, please let us know by contacting [email protected]
C2C is not available


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