Design, build, and maintain scalable data pipelines and warehouse infrastructure to support analytics and reporting needs.
Develop and maintain clean, well-modeled datasets optimized for analytics and self-service reporting.
Partner with product managers and stakeholders to define key metrics, reporting requirements, and product analytics needs.
Build and maintain BI dashboards and reports that provide visibility into product performance, operational metrics, and customer behavior.
Ensure data quality, reliability, and governance across the analytics platform.
Integrate and maintain data ingestion pipelines from internal and external systems.
Improve the data warehouse performance and data modeling layer to enable faster and more reliable analytics.
Enable self-service analytics by creating curated datasets and semantic layers for internal teams.
Document datasets, metric definitions, and data lineage to improve data discoverability and trust in data.
Collaborate with engineering teams to ensure data is captured, modeled, and surfaced effectively for analytics use cases.

Requirements

7+ years of experience in data engineering, analytics engineering, or data platform development.
7+ years of advanced SQL experience working with large datasets.
5+ years experience with programming languages such as Python, R, Go, or JavaScript.
5+ years experience with data transformation frameworks such as dbt core or similar tools.
5+ years experience leveraging cloud technologies (AWS preferred) for data pipelines, storage, and analytics.
3+ years experience with modern columnar data warehouses such as Amazon Redshift, Snowflake, or Google BigQuery.
Strong experience designing data models optimized for analytics and reporting.
Experience building BI dashboards using tools such as ThoughtSpot, Looker, Tableau, PowerBI, or similar.
Experience working with data ingestion tools such as Fivetran, AWS DMS, Kafka, Spark, or similar technologies.
Strong understanding of data governance, privacy, and access control.
Ability to translate business questions into data models, metrics, and dashboards.
Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders.
Demonstrated ability to solve complex data problems and deliver scalable solutions.

Benefits

Flexibility to work where/how you want – in-office, remote, or hybrid
Robust health and wellness benefits
401k with up to a 4% company match
Flexible and generous paid time off (FTO)
Employee Stock Purchase Program

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringanalytics engineeringdata platform developmentSQLPythonRGoJavaScriptdata transformation frameworksdata modeling

Soft Skills

communicationcollaborationproblem-solvingstakeholder engagementdata governancetrust in datatranslating business questionsself-service analyticsdocumentationdata discoverability