Senior Data Engineer

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Goods & Services

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2013

🤖 Artificial Intelligence

🏢 Enterprise

🤝 B2B

Artificial Intelligence • Enterprise • B2B

Goods & Services is a product design and digital engineering company that helps enterprises design, build, and scale AI-powered products, platforms, and customer experiences. They provide services across Data & Artificial Intelligence, Experience Strategy & Design, and Technology & Engineering (cloud, software, hardware), focusing on modernizing data infrastructure, building digital product ecosystems and global web systems, and delivering enterprise-grade cloud and platform engineering for market-leading B2B clients.

📋 Description

• End-to-End Pipeline Engineering: Design, build, and deploy scalable ETL/ELT pipelines from diverse source systems into our Snowflake Data Cloud. • Cloud Infrastructure: Manage and optimize data flows within an AWS environment (S3, Lambda, IAM), ensuring high availability, security, and cost-efficiency. • High-Scale Processing: Leverage Databricks and Python (PySpark) to handle complex data transformations and high-volume workloads. • Implement the Semantic Layer: Collaborate with the team to define, implement, and scale our Semantic Layer (via dbt Semantic Layer, MetricFlow, or similar) to standardize business logic, metrics, and dimensions for all downstream consumers. • Model for Truth: Use dbt to build modular, version-controlled, and tested data models that serve as the definitive foundation for business intelligence.

🎯 Requirements

• 5+ years of experience in data architecture, data engineering, or a closely related discipline in a complex, multi-team data environment • Data Warehousing: Expert-level proficiency in Snowflake (clustering, Snowpipe, streams, and tasks) or similar cloud data warehouses. • Analytics Engineering: Advanced mastery of dbt and complex SQL transformation logic, with specific experience building semantic models and metric definitions. • Big Data & Code: Strong Python skills and hands-on experience with Databricks for Spark-based orchestration. • Cloud Infrastructure: Practical experience managing data workloads within AWS. • Version Control: Deep understanding of Git-based workflows and CI/CD for data.