Senior dbt Developer (Analytics Engineer)

About us:

Talent has no borders. Proxify's mission is to connect top developers around the world with opportunities they deserve. So, it doesn't matter where you are; we are here to help you fast-track your independent career in the right direction. 🙂

Since our launch, Proxify's developers have successfully worked with 1200+ happy clients to build their products and growth features. 5000+ talented developers trust Proxify and its network to fulfil their dreams and objectives.

Proxify is shaped by a global network of supportive, talented developers interested in remote full-time jobs. Our Glassdoor (4.5/5) and Trustpilot (4.8/5) ratings reflect the trust developers place in us and our commitment to our members' success.

The Role:

We are looking for a Senior dbt Developer to lead the transformation of our clients' raw enterprise data into clean, high-performance, business-ready data models. In this role, you will own our clients' dbt architecture, standardizing how data is modeled, tested, documented, and deployed across their entire cloud data warehouse.

This role requires an engineer who treats analytics code like software: using version control, writing automated tests, optimizing warehouse compute costs, and implementing continuous integration (CI) pipelines. You will transform complex pipelines into dry, modular data environments that enable fast, accurate business decision-making.

What we are looking for:

• 3+ years of deep, hands-on production experience architecting complex dbt Core or dbt Cloud projects.
• Master-level proficiency in writing highly complex, optimized, and readable SQL. Deep understanding of dimensional modeling (Kimball methodology), Data Vault 2.0, or wide-table strategies for analytics.
• Proven track record in configuring and managing large datasets within modern platforms like Snowflake, Google BigQuery, or Databricks.
• Strong version control experience using Git and setting up automated CI/CD workflows (e.g., Slim CI via GitHub Actions or GitLab CI) to test data changes before production deployment.
• Experience extending dbt functionality using Jinja templating, writing custom macros, and implementing standard packages (such as dbt_utils, dbt_expectations, or codegen).
• Proficiency in Python for writing advanced dbt extensions, orchestrating custom scripts, or building data extraction workflows.

Nice-to-Have:

• Official dbt Certified Developer credential.
• Experience with data orchestrators like Apache Airflow, Prefect, or Dagster.
• Knowledge of data quality and observability platforms (e.g., Monte Carlo, Great Expectations, or Elementary).
• Experience managing dbt Semantic Layer or building metrics definitions for self-service BI environments (like Looker, Tableau, or Lightdash).

Responsibilities:

• Architect, optimize, and maintain scalable dbt models (Sources, Staging, Marts) that cleanly map raw source data to final analytical layers.
• Profile and optimize slow-running dbt models by tuning materialization strategies (Incremental models, Ephemeral layers, Cluster keys, and Partitioning).
• Establish strict data quality testing frameworks within dbt to catch data anomalies, schema drifts, and edge cases before they reach downstream business applications.
• Maintain high-quality dbt documentation and comprehensive lineage graphs, making data structures discoverable and clear for downstream business analysts.
• Run peer code reviews, establishing structural conventions for model naming, project organization, and compute cost control across the data team.

What we offer:

Get paid, not played

No more unreliable clients. Enjoy on-time monthly payments with flexible withdrawal options.

Predictable project hours

Enjoy a harmonious work-life balance with consistent 8-hour working days with clients.

Flex days, so you can recharge

Enjoy up to 24 flex days off per year without losing pay, for full-time positions found through Proxify.

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Compensation

Enjoy the same pay, every month with positions landed through Proxify.