Analytics Engineer

Sweed POS

. Build and maintain analytics data models using dbt - incremental pipelines (merge strategies, hashdiff, SCD Type 1/2) across retail domains (sales, inventory, loyalty, marketing, promotions), with strong emphasis on structure, documentation, and maintainability .

Posted 4/21/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftBigQueryCloudSQL

About the role

Key responsibilities & impact

Build and maintain analytics data models using dbt - incremental pipelines (merge strategies, hashdiff, SCD Type 1/2) across retail domains (sales, inventory, loyalty, marketing, promotions), with strong emphasis on structure, documentation, and maintainability
Implement data quality tests and validation logic, ensuring accuracy and trust across reporting layers
Own conformed dimensions as shared contracts across downstream consumers
Collaborate with the Data Architect to apply consistent modeling standards and support architecture evolution
Work with internal teams and sometimes clients to clarify requirements and align on metric logic
Translate business needs into robust, reusable data models
Ensure the integrity of client-facing reports, including reliability, freshness, and metric correctness
Contribute to clear documentation, metric definitions, and data contracts
Support the continuous improvement of our modern data stack: dbt, Trino, ClickHouse, Airflow, Cube.dev, Metabase

Requirements

What you’ll need

5+ years of experience in analytics engineering, data engineering, or BI development
Strong SQL skills and hands-on experience with dbt
Solid understanding of data modeling for analytics/reporting, including fact/dimension and SCD patterns design
Experience writing and maintaining data quality tests (e.g. dbt tests, custom SQL assertions, test coverage frameworks)
Experience with modern cloud-based data warehouses (e.g. Snowflake, ClickHouse, Redshift, BigQuery)
Excellent spoken and written English — you’ll communicate with internal teams and sometimes with external clients
Grain fluency - instinct for when a join will fan out, double-count, or drop rows
Reconciliation thinking - can trace a wrong mart number back to its source
Metric definition - translates ambiguous asks into precise, defensible definitions
Ability to clearly explain data logic and metric definitions to non-technical stakeholders
Meticulous approach to documentation, testing, and ownership of data artifacts

Benefits

Comp & perks

100% remote – We’re a remote-first company, no offices needed!
Flexible working hours – Core team time: 09:00-15:00 GMT (flexible per team)
20 paid vacation days per year
12 holidays per year
3 sick leave days
Medical insurance after probation
Equipment reimbursement (laptops, monitors, etc.)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLdbtdata modelingdata quality testsfact/dimension designSCD patternsdata warehousesSnowflakeClickHouseBigQuery

Soft Skills

communicationdocumentationmeticulousnesscollaborationmetric definitionreconciliation thinkinggrain fluencyexplanation skills