Senior Analytics Engineer
New
B
BetterHelpOnline therapy
Location: US - Remote, We operate on PST and candidates in any time zone are welcome to apply.Full-TimeSenior
SalaryThe base salary range for this position is $135,000 - $155,000. In addition to the base salary, this position is eligible for a performance bonus
Apply NowOpens the employer's application page
Job Details
- Experience
- At least 5 years of experience in analytics engineering, data engineering, data analytics, or a related field; at least 4 years of experience working with business intelligence (BI) tools, preferably Looker or Omni; at least 3 years of experience using dbt for in-warehouse data transformations
- Required Skills
- PythonSQLGitSnowflakedbtLooker
Requirements
- At least 5 years of experience in analytics engineering, data engineering, data analytics, or a related field.
- At least 4 years of experience with business intelligence tools, preferably Looker or Omni.
- At least 3 years of experience using dbt for in-warehouse data transformations.
- Strong SQL skills, including big-data-scale query design, incrementality patterns, and performance optimization.
- Deep understanding of analytical data modeling frameworks and tradeoffs, including star schemas and dimensional modeling.
- Experience with data testing, including assertion design, coverage, orchestration, and data contracts.
- Experience using Git for version control in a collaborative team environment.
- Experience providing mentorship, supporting collaborative development, and conducting team pull request reviews.
- A BS/MA in a quantitative discipline such as Computer Science, Statistics, Mathematics, or Engineering is preferred.
- Experience with dimensional modeling at big data scale, semantic or metrics layers, data privacy and governance, Python, or web-based B2C analytics is a plus.
Responsibilities
- Design and build trusted data warehouse tables with SQL and dbt for business intelligence, data science, and machine learning use cases.
- Lead dimensional modeling from requirements gathering through implementation, testing, and delivery.
- Extend the semantic layer using Snowflake semantic views in dbt, defining canonical metrics, relationships, and verified queries.
- Translate stakeholder needs into data models and downstream experiences in Looker.
- Enable data-driven decisions through dashboards, self-service tooling, and ad hoc analyses for cross-functional teams.
- Apply PII/PHI classification, masking policies, and data contracts to protect and govern data assets.
- Optimize models for performance and cost using incrementality patterns, warehouse and clustering choices, and query optimization.
- Improve data self-service, discovery, and lineage, and collaborate with data and machine learning engineers.
View Full Description & ApplyYou'll be redirected to the employer's site
