Note: The job is a remote job and is open to candidates in USA. SharkNinja is a global product design and technology company developing lifestyle solutions under the Shark and Ninja brands. The Senior Analytics Engineer owns data products end to end, including source onboarding, pipeline orchestration, data modeling, testing, and analytics delivery. The role also establishes engineering standards, ensures pipeline reliability, mentors junior engineers, and uses AI-assisted development tools responsibly.
Responsibilities
- Onboard new sources end to end: vendor REST APIs, SFTP and S3 file drops, on-prem file shares
- Handle pagination, rate limits, retries, and incremental extracts
- Design connection auth: key-pair, token rotation, environment-variable contracts
- Actively work with vendors and source owners on access, file cadence, and schema changes
- Lead orchestration pipeline orchestration: schedules, backfills, and various checks and tests
- Account for partitioned incremental loads, deliberate concurrency
- Build idempotent loads with an explicit merge grain, so a failed run is fixed by re-running it
- Own alerting, triage, and root cause on failed runs
- Keep warehouse sizing and query cost in check
- Write Python tests, dbt tests, keep CI green
- Set the standards: module structure, config and secrets, and what a pipeline needs before it ships
- Write them down and enforce them in code review
- Build and maintain dbt Cloud models on Snowflake, from staging through marts, with tests and docs, following repo standards
- Write reusable dbt macros with Jinja to keep models DRY and consistent
- Use the available AI tools for dbt models, SQL refactoring, scaffolding, and docs
- Review and test everything they produce
- Document how the team should use these tools, and what not to hand them
- Git and code review, mentoring junior engineers, and following our dependency and data governance policies
Skills
- You'll need strong SQL and hands-on Python coding experience, along with solid working knowledge of Snowflake, dbt Cloud, and an orchestrator like Dagster or Airflow
- Expert SQL and deep familiarity with Snowflake
- Real depth in ETL/ELT and data modeling, with dbt Cloud experience
- Hands-on with Dagster or Airflow, including partitioning and backfills
- Pipelines you designed that kept working as volume grew
- Third-party APIs and file feeds pulled into a warehouse, plus the auth and secret management around them
- Owned pipeline reliability in production: alerting, triage, and follow-through after an incident
- Set or raised engineering standards on a team, in writing, and made them stick
- Used AI coding assistants in a real production workflow, with judgment about where they help and where they cause trouble
- Clear communication with non-engineers, vendors and stakeholders
- Bachelor's degree in Computer Science, Data Science, Engineering, or related field, or equivalent practical experience
- 3-5 years of experience in data engineering and analytics
- Having written the guardrails for a team is a plus
- Advanced degrees or professional certifications related to data engineering are preferred
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Flexible spending accounts
- Health savings accounts (HSA) with company contribution
- 401(k) retirement plan with matching
- Employee stock purchase program
- Life insurance
- AD&D
- Short-term disability insurance
- Long-term disability insurance
- Generous paid time off
- Company holidays
- Parental leave
- Identity theft protection
- Pet insurance
- Pre-paid legal insurance
- Back-up child and eldercare days
- Product discounts
- Referral bonus program
- Competitive health insurance
- Retirement plans
- Wellness programs
- Learning Programs
- Career acceleration
- Remote US
Company Overview
Company H1B Sponsorship