Senior Analytics Engineer at SharkNinja in United States

Job description

• This role owns data products end to end: onboarding a new source, orchestrating it, modeling it, and delivering something a business team can act on.
• 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. We work in an AI-assisted environment and expect this role to use AI coding tools daily, without lowering the bar on correctness or governance.

Responsibilities

• Onboarding new data sources
• 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
• Reliable, scalable pipelines
• 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
• Testing and standards
• 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
• Modeling and analytics
• 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
• AI-assisted development
• 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
• Team practices
• Git and code review, mentoring junior engineers, and following our dependency and data governance policies

Requirements

• 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. Having written the guardrails for a team is a plus
• Clear communication with non-engineers, vendors and stakeholders
• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field, or equivalent practical experience.
• Advanced degrees or professional certifications related to data engineering are preferred
• 3-5 years of experience in data engineering and analytics

Skills

Required

• Expert SQL
• Deep familiarity with Snowflake
• Real depth in ETL/ELT and data modeling
• dbt Cloud experience
• Hands-on with Dagster or Airflow
• Partitioning and backfills
• Third-party APIs and file feeds
• Auth and secret management
• Pipeline reliability in production

Benefits

• We offer competitive health insurance, retirement plans, paid time off, employee stock purchase options, wellness programs, SharkNinja product discounts, and more. We empower your personal and professional growth with high impact Learning Programs featuring bold voices redefining what’s possible. When you join, you’re not just part of a company—you’re part of an outrageously extraordinary community. Together, we won’t just launch products—we’ll disrupt entire markets.
• Salary and Other Compensation: The annual salary range for this position is displayed below. Factors which may affect starting pay within this range may include geography/market, skills, education, experience and other qualifications of the successful candidate.
• The Company offers the following benefits for this position, subject to applicable eligibility requirements: 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, and more.
• $116,300 - $155,000 USD