Data Engineer
New
S
Scale MediaEcommerce data
Source API remote eligibility restrictions: United StatesFull-TimeMiddle
Salary130,000 - 150,000 USD per year
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Job Details
- Experience
- 3–5 years of experience in data engineering or a closely related role.
- Required Skills
- AWSPythonSQLSnowflakeAirflowBigQuerydbtRedshift
Requirements
- Have 3–5 years of experience in data engineering or a closely related role.
- Bring strong SQL and Python skills and hands-on experience building and maintaining production data pipelines.
- Have experience with orchestration and transformation tools such as Airflow and dbt.
- Have experience with a cloud data warehouse such as Snowflake, BigQuery, or Redshift.
- Have hands-on Odoo experience, including its data model, integrations, and supporting or executing version upgrades.
- Have experience working with Shopify data and APIs.
- Have experience integrating ecommerce and marketing platforms such as Amazon Seller Central, Meta, Google Ads, or Klaviyo.
- Be comfortable managing cloud infrastructure such as AWS or GCP, along with scripts and jobs running on it.
- Understand data governance, security, and access-control practices.
- Document systems clearly and explain data systems to non-technical teammates.
Responsibilities
- Own and optimize the company’s data architecture and ETL/ELT pipelines, including scheduling, orchestration, and monitoring.
- Maintain, optimize, and expand hosting infrastructure and scripts as data volume and use cases grow.
- Ensure accuracy, consistency, and reliability across source systems.
- Maintain API integrations and data connectors for Shopify, Amazon Seller Central, Meta, Google Ads, and Klaviyo.
- Scope and build new data integrations as the business adds tools, channels, and brands.
- Partner with the inventory team on Odoo initiatives and plan and execute Odoo upgrades.
- Design, build, and maintain integrations and ETL processes between Odoo and other systems.
- Oversee data governance, access controls, security practices, and documentation.
- Partner with analytics and marketing teams to define and standardize business-critical KPIs.
- Implement AI/ML-driven data solutions and connect the data warehouse to an LLM through MCP.
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