Job description
Analytics Engineer
Job Type: Full-Time
Work Mode: Fully Remote
Location: San Francisco, CA, United States
Experience: 3–8 Years
Salary: $110,000 – $165,000 per year
Employment Type: Permanent
Job Summary
We are looking for a talented Analytics Engineer to transform raw data into reliable, well-structured, and actionable datasets that support business intelligence, reporting, and strategic decision-making.
The ideal candidate will have strong experience in SQL, dbt, data modeling, cloud data warehouses, and modern analytics engineering practices. You will collaborate with data engineers, data analysts, product managers, and business stakeholders to develop scalable analytics solutions.
Key Responsibilities
Design, develop, and maintain scalable data transformation pipelines.
Build and manage data models using SQL and dbt.
Transform raw datasets into clean, reliable, analytics-ready data.
Develop and maintain data warehouses and data marts.
Create reusable data models for business intelligence and reporting.
Implement data quality testing, validation, and monitoring.
Optimize SQL queries and improve data warehouse performance.
Integrate data from multiple business applications and platforms.
Collaborate with data analysts and business teams to understand reporting requirements.
Maintain documentation for data models, workflows, and transformations.
Ensure data consistency, accuracy, governance, and security.
Support dashboards, KPI reporting, and business analytics initiatives.
Required Technical Skills
Programming: Advanced SQL, Python.
Analytics Engineering: dbt Core, dbt Cloud.
Data Warehousing: Snowflake, Google BigQuery, Amazon Redshift.
Data Modeling: Dimensional modeling, Star Schema, Snowflake Schema.
ETL/ELT: Data transformation, pipeline development, data integration.
BI & Visualization: Tableau, Power BI, Looker, Looker Studio.
Cloud Platforms: AWS, Azure, or Google Cloud Platform.
Data Orchestration: Apache Airflow, Dagster.
Version Control: Git, GitHub, GitLab.
Data Quality: Great Expectations, dbt tests, data validation.
Qualifications
Bachelor's degree in Computer Science, Information Technology, Data Analytics, or a related field.
3–8 years of experience in Analytics Engineering, Data Engineering, or a related role.
Strong expertise in SQL and data transformation.
Hands-on experience with dbt and modern data warehouse platforms.
Experience developing scalable and reusable data models.
Understanding of data architecture, ETL/ELT workflows, and analytics best practices.
Strong analytical, communication, and problem-solving skills.
Ability to work independently in a fully remote environment.
Preferred Qualifications
Experience implementing modern data stack architectures.
Knowledge of business intelligence and reporting frameworks.
Experience working with large-scale datasets.
Understanding of data governance and data privacy.
Experience with CI/CD workflows for analytics projects.
Familiarity with Agile development methodologies.
Salary & Benefits
Annual Salary: $110,000 – $165,000.
Competitive compensation based on experience and skills.
Fully remote working opportunity.
Health, dental, and vision insurance (subject to employer policy).
Paid vacation and holidays.
Professional development opportunities.
Career growth and advancement opportunities.
Work Schedule
Employment Type: Full-Time, Permanent.
Working Hours: 40 hours per week.
Work Location: Fully Remote.
Location Preference: San Francisco, CA, United States.
Must be available to collaborate with US-based teams.
Equal Employment Opportunity
We are an equal opportunity employer. All qualified applicants will receive consideration for employment without discrimination based on legally protected characteristics.
Apply Now: Submit your updated resume highlighting your SQL, dbt, data modeling, and analytics engineering experience.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.