Data Engineer

About Us

Global Parachutes is a full-service Amazon Marketing Agency that partners with brands across the globe to accelerate their growth on Amazon. We specialize in crafting strategies that drive performance and help our clients achieve their business goals on the world's largest e-commerce platform.

Job Overview

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We are seeking a highly skilled Analytics Engineer to own the entire data lifecycle for our agency, from ingestion to visualization. This role is a hybrid of Data Engineering and Business Intelligence (BI), responsible for building and maintaining our custom, scalable Amazon data pipelines and developing high-impact client-facing dashboards.

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This is a critical role to move our reporting beyond manual processes and into a robust, centralized data platform like Microsoft Fabric or Azure.

Key Responsibilities

I. Data Engineering & Pipeline Development (Infrastructure Focus)

• Custom Data Ingestion: Design, build, and maintain automated data pipelines using Python to connect directly to the Amazon Selling Partner API (SP-API).

• Cloud & Security: Utilize Microsoft Fabric or Azure services (e.g., Azure Data Factory, Azure Functions, Synapse) to orchestrate, schedule, and secure data movement and storage.

• Data Lakehouse Management: Load and transform raw SP-API data into a clean, structured format (e.g., Delta Lake/Parquet) within a Data Lakehouse environment for optimal query performance.

• Process Automation: Go beyond reporting by identifying and automating repetitive manual processes agency-wide, ensuring data quality and consistency

II. Business Intelligence & Reporting (Analysis Focus)

• Data Modeling: Develop robust, scalable Star Schema data models within Power BI to unify data from Amazon, advertising platforms, and finance systems.

• Advanced Dashboarding: Design, develop, and maintain high-impact Power BI dashboards and reports that showcase key client performance indicators (KPIs) and actionable insights.

• Complex Calculations (DAX): Write expert-level DAX (Data Analysis Expressions) for complex financial calculations (e.g., True Profit & Loss, Customer Lifetime Value, and proprietary agency metrics).

• Data Governance: Maintain accurate, organized, and clean datasets to ensure accuracy and consistency across all business-critical reports.

III. Collaboration & Continuous Improvement

• System Optimization: Continuously assess and proactively suggest improvements or updates to the existing automation solutions, reports, and underlying data architecture.

• Training & Support: Support cross-functional teams with data, reports, and insights, and train team members on new dashboard functionality.

Required Skills & Qualifications

• Must-Have Core Skills (The Hybrid Skill Set)

• Cloud Data Engineering: Proven experience with Python for API integration and data transformation (JSON parsing).

• Platform Expertise: Hands-on experience with Microsoft Fabric or components of the Microsoft data stack (Azure Data Factory, Azure Synapse, or Databricks).

• Advanced BI: Expert proficiency in Power BI for visualization, data modeling, and writing advanced DAX for complex metrics.

• Data Structuring: Deep understanding of relational databases and data warehousing concepts (Star/Snowflake schema) and advanced SQL or PySpark.

• E-commerce Domain: Strong knowledge of Amazon Seller Central, Campaign Manager data, and core e-commerce metrics (ACOS, ROAS, Inventory Management).

• Nice-to-Have Technical Skills

• Experience with cloud storage (Azure Data Lake Storage Gen2 or AWS S3).

• Knowledge of OAuth 2.0 for API authentication and best practices for managing client credentials securely (e.g., Azure Key Vault).

• Experience with high-volume ETL/ELT workflows.