Posted 4 days ago 66 views Report Job
A leading US-based Fruit Ingredients & Sourcing company is looking for a Mid-Level Data Engineer to join its growing Data & Analytics Team.
This role is ideal for someone passionate about SQL, Data Warehousing, Data Modeling, and Business Intelligence, with the ability to build scalable data solutions for enterprise reporting and analytics.
Responsibilities
Key Responsibilities
- Develop and optimize complex SQL queries, Views, and CTEs.
- Design and maintain semantic data models for reporting and analytics.
- Build and optimize Data Warehouse objects and backend reporting solutions.
- Analyze query performance and optimize execution plans.
- Validate data accuracy and reconcile data across multiple systems.
- Work with large datasets and complex relational database structures.
- Collaborate with BI Developers and business stakeholders to translate business requirements into technical solutions.
- Support Power BI datasets and enterprise reporting initiatives.
Required Skills
- 2–4 years of experience in SQL development and Data Warehousing.
- Strong proficiency in Oracle SQL or SQL Server.
- Excellent understanding of:
Complex Joins
CTEs & Views
Window & Aggregate Functions
Query Optimization & Performance Tuning
Relational Database Design
Data Modeling (Star Schema / Snowflake Schema)
ETL / ELT concepts
Data Validation & Reconciliation
- NetSuite Analytics Warehouse (NSAW)
- Suite Analytics Connect / Saved Searches
- Working knowledge of Power BI (Power Query & Data Modeling).
- Strong analytical, troubleshooting, and communication skills.
Preferred Skills
Experience with any of the following will be a strong advantage:
- Oracle Database
- NetSuite ERP
- Data Warehouse & Semantic Layer development
- Power BI
- Python (basic)
- Azure, AWS, or GCP
Exposure to NetSuite business processes is highly desirable, including:
- Sales Orders
- Purchase Orders
- Transaction Lines
- Item Fulfillment
- Inbound Shipments
- Saved Searches
- Data reconciliation between NetSuite and NSAW
Skills
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