Data Engineer - Snowflake/DBT SME (Remote)

TM Floyd and Company

• $110K — $130K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 8-10 years of progressive data engineering experience, with at least 3 years in a senior or lead role.
  • 5 years of experience in designing and optimizing solutions in Snowflake, including SQL development and data modeling.
  • Hands-on experience with dbt for building data products and CI/CD integration.
  • Proficient in SQL and Python for data engineering tasks.
  • 3 years of experience with pipeline orchestration tools.
  • Experience in semantic layer development in Snowflake.
  • Strong communication skills to translate business needs into technical solutions.

Responsibilities

  • Architect and deliver enterprise data platform solutions using Snowflake, dbt, SQL, and Python.
  • Establish data engineering standards and governance frameworks for quality and security.
  • Collaborate with business stakeholders to translate requirements into actionable data solutions.
  • Lead the support and continuous improvement of data platforms, resolving complex issues.
  • Provide mentorship and strategic direction for the data engineering team.

Benefits

  • Generous array of benefits based on assignment length.
  • Referral bonus of up to $1,000.
Full Job Description
We're looking for aData Engineer - Snowflake/DBT SME for a remote role.

Ideal Candidate:
The ideal candidate is a strong communicator and a senior Snowflake and DBT expert with strong data modeling and semantic layer experience who can build scalable, AI-ready datasets and analytics solutions. They combine deep technical expertise with excellent communication skills, partnering effectively with business stakeholders while mentoring and guiding other engineers. Experience with Snowflake Cortex, AI/ML, and modern analytics engineering practices is a strong plus. MUST be US Citizen or Green Card holder.

Work Authorization: U.S. citizens and Green Card holders only. Sponsorship is not available for this role; no C2C or third-party candidates. Candidates must be able to work on our W2.

Skills & Qualifications:
  • 8-10 years of progressive data engineering experience, with at least 3 years in a senior or lead technical capacity
  • 5 years of experience:
    • Designing, developing, and optimizing solutions in Snowflake, including SQL development, data modeling, performance tuning, security/access patterns, and production support
    • Serving in a senior engineer, technical lead, solution lead, or architecture-influencing capacity
    • Working hands-on with dbt, including building data products, model development, testing, documentation, macros, environment promotion, and CI/CD integration
    • Using SQL and Python for data engineering, automation, transformation, and data quality validation
  • 3 years of experience with pipeline orchestration tools
  • Experience with semantic layer development in Snowflake
  • Experience working with the data science side of the business
  • Fluent in business language and able to meet with lines of business (finance, marketing, etc.) and translate requirements between them and engineering.
  • Experience with streaming, lakehouse architecture, metadata management, data observability, or AI/ML data preparation is preferred
  • Demonstrated experience architecting ML/AI data infrastructure including feature stores, MLOps pipelines, and LLM-based data processing workflows
  • Prior experience in financial services, banking, or another regulated industry is strongly preferred

Key Responsibilities:
  • Architect, design, and deliver enterprise data platform solutions leveraging Snowflake, dbt, SQL, Python, and modern data integration technologies, ensuring scalable, secure, reliable, and maintainable data pipelines and analytical data products
  • Establish and enforce data engineering standards, best practices, and governance frameworks for code quality, CI/CD, data testing, observability, documentation, metadata management, security, and operational excellence
  • Partner with business stakeholders, data owners, architects, compliance teams, and technology partners to translate business requirements into data solutions, data models, integration patterns, and implementation roadmaps that deliver measurable business value
  • Lead the support, monitoring, and continuous improvement of enterprise data platforms by resolving complex production issues, improving performance, enhancing data quality, and ensuring operational reliability
  • Provide technical leadership, mentorship, and strategic direction for the data engineering practice, including architectural reviews, coaching engineers, evaluating emerging technologies, and supporting advanced analytics, AI/ML, and enterprise data initiatives

Education/Certifications:
  • Minimum: Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field, or equivalent combination of education and relevant professional experience
  • Preferred: Master's degree in Computer Science, Data Engineering, Information Systems, Data Science, or related discipline
  • Preferred: Cloud data platform certification such as AWS Certified Data Analytics - Specialty, Microsoft Certified: Azure Data Engineer Associate, GCP Professional Data Engineer, or Snowflake SnowPro Certifications (Core, Associate, Advanced)
  • Preferred: DBT Certification or equivalent analytics engineering credential

We offer a generous array of benefits, depending on the length of assignment. We also offer a referral bonus of up to $1,000. Ask us for more details!

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