Senior Analytics Engineer, SharkNinja
$116.3-155k
+ ESPP
Home devices and appliances
Job no longer available
Home devices and appliances
1001+ employees
Job no longer available
$116.3-155k
+ ESPP
1001+ employees
Company mission
To positively impact people's lives every day in every home around the world.
Role
Who you are
- 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. 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
What the job involves
- 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
- 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
- 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
Our take
With more people looking for home products that work harders and smarter, SharkNinja has become a household name. Through its Shark line of cleaning and home care tools and Ninja range of kitchen appliance the company creates solutions that simplify daily routines and overall enhance modern living.
SharkNinja has been in operation since 1994, which is testament to the quality and popularity of its products. Since its initial launch in Canada, the company has expanded into the US and the UK. In 2017 SharkNinja was bought by CDH Private Equity for over $1.5 Billion, further proof of its impressive market value. Perhaps more evidence is that it brings in annual revenues of around $4B.
It continues to hold a strong position in the home appliance market too, competiting with big brands like Dyson. Its Shark line lead the US upright vacuum, segment, while its presence in robotics vacuums reflects steady growth in a compeititve space. Since going public, the company has m,aintained a rapid pace of innovation, launching numerous new products eacxh pear and expanding into adjecent categories such as outdoor coolers and grills. With a growing global footprint and a focus ons mart design, usabiluity, and category expansion, SharkNinja is very well positioned to continue shaping the futur of home appliances.
Freddie
Company Specialist at Welcome to the Jungle
Insights
10% employee growth in 12 months
Company
Company HQ
Needham Heights, Needham, MA
Leadership
Mark Rosenzweig
(Founder)Founded SharkNinja in 1994. Has won three Red Dot Awards for product Design.
Mark Barrocas
(CEO)Mark joined SharkNinja in 2008 as CEO. Prior to this, he spent 3 years at Aramark Uniform Services as the President of the WearGuard Division. Prior to that, he spent 4 years at Broder Bros as the President and 2 years at Perry Ellis International as VP of Corporate Sales.
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