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Numentica

Sr. Data Analytics Engineer

Company: Numentica

Location: Burbank, CA

Posted on: October 28

Job Description

City: Glendale, CA/ Burbank, CA

Onsite/ Hybrid/ Remote: Onsite (4 days a week)

Duration: 12 months

Rate Range: Up to$96/hr on W2 depending on experience (no C2C or 1099 or sub-contract)

Work Authorization: GC, USC, All valid EADs except OPT, CPT, H1B

Must Have:

  • Expert-level SQL (data modeling, optimization, query performance)
  • Hands-on experience with Snowflake
  • dbt for data transformation and analytics modeling
  • Proficiency in Python for scripting and automation
  • Familiarity with AWS cloud services
  • Version control using GitHub/GitLab
  • Experience in Agile/Scrum environments

Responsibilities:

  • Build and maintain analytical data models and assets within Snowflake, transforming raw data into trusted, consumable datasets.
  • Partner with Product Managers and stakeholders to translate business requirements into scalable data products.
  • Develop and manage transformation workflows using dbt and SQL for analytics use cases.
  • Ensure quality and performance of data assets through query optimization and validation.
  • Collaborate with Data Architects, SRE, and Platform teams within an Agile pod structure.
  • Support model deployment, version control, and documentation using Git-based workflows.
  • Maintain communication and alignment with cross-functional partners, ensuring deliverables meet evolving business needs.

Qualifications:

  • Bachelors degree in Computer Science, Information Systems, or a related STEM field (required).
  • 5+ years of experience as an Analytics Engineer or Data Engineer in enterprise-scale environments.
  • Strong understanding of data warehousing principles, dimensional modeling, and pipeline design.
  • Working knowledge of AWS ecosystem (e.g., S3, Lambda, Glue).
  • Strong communication and collaboration skills, with the ability to manage multiple priorities in a fast-paced environment.
  • Experience working in Agile/Scrum teams with structured DevOps processes (pull requests, merge requests, version control).

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