Senior Data Platform Engineer
Goods & Services Mexico, Chihuahua, Mexico
Business Consulting and Services · 201-500 employees
About the role
The Senior Data Platform Engineer will design, build, and maintain modern lakehouse platforms, specifically focusing on Microsoft Fabric and OneLake. They are responsible for ensuring data quality, reliability, and performance throughout the full data lifecycle from ingestion to production support.
What they look for
Requirements
Candidates must have at least 5 years of experience in data warehouse or lakehouse projects with proficiency in Python, Spark, and SQL. A deep understanding of Delta table concepts and dimensional data modeling is required, along with the ability to manage the full development lifecycle.
Full description
About Goods & Services
Goods & Services is a product design and engineering company.
We solve mission-critical challenges for some of the world’s largest enterprises, with deep expertise in highly regulated industries—including life sciences and financial services. Our design-led approach allows us to apply cutting-edge capabilities in AI, Data and Hardware Engineering to companies of any size.
Headquartered in the United States, we operate regional development centers in Mexico and the United Kingdom. This global footprint—anchored by our nearshore model—enables us to deliver at scale with the speed, efficiency, and cultural alignment our clients expect.
About the job
Goods & Services is looking for a Senior Data Platform Engineer who is responsible for hands-on implementation, maintenance, and operational support of modern lakehouse platforms, with a focus on Microsoft Fabric / OneLake.
In this role, you will participate in the full lifecycle from requirements to deployment and production support, translating business needs into reliable data products while ensuring data quality, monitoring, and performance. You will work closely with Solution Architects to follow platform standards across multiple engagements.
What you’ll do:
- Ensure data quality and reliability by implementing data quality checks, monitoring anomalies, performing root cause analysis on pipeline failures, and proactively identifying and resolving data or process issues impacting reliability, cost, or stakeholder trust.
- Implementation & Operations: Design, build, and maintain data ingestion and orchestration components (e.g., Fabric Data Pipelines, notebooks) for patterns such as file drops, APIs, and database extracts.
- Reliability & Quality: Ensure data integrity by implementing quality checks, monitoring anomalies, and performing root cause analysis on pipeline failures.
- Architecture & Modeling: Develop curated transformation layers (Silver/Gold) aligned to defined grains and keys to publish reliable data products.
- Operational Excellence: Operate and monitor platform components (schedules, alerts, runbooks) and maintain accurate “as-built” technical documentation.
- Stakeholder Collaboration: Work with analytics/BI teams to ensure datasets support reporting needs and assist with validation and adoption.
What you’ll need:
- 5+ years’ years in Business Intelligence, Data Warehouse, or Lakehouse projects.
- Proficiency in Python or Spark-based transformations and strong SQL skills for complex query analysis.
- Experience with Microsoft Fabric (preferred) or similar cloud data environments and orchestration tools.
- Deep understanding of Delta table concepts (partitioning, schema evolution) and dimensional data modeling (grain/keys).
- Proven ability to manage the full development lifecycle and troubleshoot performance problems across ingestion and consumption layers.
- Ability to express complex technical concepts in business terms and work effectively in a team environment.
Nice to have:
- Familiarity with reporting/semantic consumption patterns (Power BI familiarity is a plus).
- Comfort working in a client-services environment (multiple engagements, shifting priorities, clear communication, strong documentation).
- Knowledge of multi-unit retail/restaurant analytics is helpful but not required.
