Data Engineer (Contract)

Overview

We are seeking a highly experienced Data Engineer to support a fast-growing eCommerce brand operating within a modern, warehouse-first data architecture. This is a project-based, on-demand engagement for a senior-level professional who can design, build, and optimize scalable data infrastructure across analytics, marketing, and operational workflows.

The ideal candidate has deep expertise in BigQuery, dbt, and Looker, with hands-on experience modeling complex eCommerce data from platforms such as Shopify, Klaviyo, subscription systems (e.g., Loop), and 3PL providers

Key Responsibilities

• Design, build, and maintain scalable data pipelines using BigQuery and dbt

• Architect and optimize warehouse-first data models to support analytics, marketing, and operational reporting

• Develop and maintain Looker dashboards and semantic layers

• Integrate and transform data from Shopify, Klaviyo, Loop (subscriptions/returns) and 3PL systems (e.g., ShipHero, ShipBob, etc.)

• Build automated workflows for data ingestion, validation, and monitoring

• Implement best practices for data quality, governance, and documentation

• Leverage AI tools (LLMs, automation frameworks) to:

• Accelerate data transformation workflows

• Refactor and optimize SQL/dbt models

• Automate anomaly detection and QA processes

• Collaborate with analytics, product, and marketing teams to translate business requirements into scalable data solutions

• Troubleshoot data discrepancies and provide root-cause analysis

• Recommend architectural improvements to improve performance, reliability, and scalability

Service Level Agreements (SLAs)

• Response Time: Acknowledge requests within 24 hours

• Critical Issues (P0): Immediate response and active resolution

• Standard Requests: Timeline provided within 72 hours

• Billing Model: Time & materials based on agreed scope and hours worked

Requirements

• 5+ years experience in data engineering within a modern cloud data stack

• Advanced experience with BigQuery, Dbt, SQL performance optimization

• Experience building and maintaining Looker dashboards and data models

• Strong understanding of:

• eCommerce metrics (AOV, LTV, churn, CAC, retention)

• Marketing attribution

• Subscription data structures

• Experience integrating and modeling data from (not exactly similar software would work) Klaviyo, Loop or similar subscription platforms, Shopify 3PL systems

• Experience implementing data quality checks and validation pipelines

• Strong written and verbal communication skills

• Ability to work independently with minimal oversight

Preferred Qualifications

• Experience working with distributed or agency environments

• Experience supporting DTC brands

• Experience with marketing data pipelines (Google Ads, Meta, TikTok)

• Experience building reverse ETL workflows

• Familiarity with data ingestion tools (Fivetran, Daton, Airbyte, etc.)

• Experience implementing AI-assisted data transformation workflows

• Exposure to experimentation analytics (A/B testing frameworks)

Ideal Candidate Profile

We are looking for someone who:

• Understands both technical architecture and business implications

• Can move quickly in a project-based environment

• Thinks in systems, not just SQL queries

• Is comfortable leveraging AI tools to improve speed and efficiency

• Has experience working across marketing, product, and operations data

The duties and responsibilities described here are not a comprehensive list and the scope of the job may change as necessitated by business demands. Anatta Design reserves the right to revise the job description as circumstances warrant.

Compensation Transparency & Pay Philosophy

At Anatta Design, we believe in fair and competitive compensation based on location. We post salary ranges in compliance with state requirements for U.S.-based roles, ensuring transparency for candidates in those regions. If you are applying from outside the U.S., please note that our pay scales are adjusted based on the cost of living and market conditions in each country.