Data Warehouse Engineer

Job Description

Job_Description”:”

Pando is a global leader insupply chain technology, building the worlds quickest time-to-valueFulfillment Cloud platform. Pando\u2019s Fulfillment Cloud providesmanufacturers, retailers, and 3PLs with a single pane of glass tostreamline end-to-end purchase order fulfillment and customer order fulfillmentto improve service levels, reduce carbon footprint, and bring down costs.As a partner of choice for Fortune 500 enterprises globally, with apresence across APAC, the Middle East, and the US, Pando is recognized as aTechnology Pioneer by the World Economic Forum (WEF), and as one of thefastest growing technology companies by Deloitte.

Role Overview

As a Junior Data WarehouseEngineer at Pando, you\u2019ll work within the Data & AI Services team tosupport the design, development, and maintenance of data pipelines andwarehouse solutions. Youll collaborate with senior engineers andcross-functional teams to help deliver high-quality analytics and reportingsolutions that power key business decisions. This is an excellent opportunityto grow your career by learning from experienced professionals and gaininghands-on experience with large-scale data systems and supply chaintechnologies.

Key Responsibilities

• Assist in building and maintaining scalable data pipelines using tools like PySpark and SQL-based ETL processes.
• Support the development and maintenance of data models for dashboards, analytics, and reporting.
• Help manage parquet-based data lakes and ensure data consistency and quality.
• Write optimized SQL queries for OLAP database systems and support data integration efforts.
• Collaborate with team members to understand business data requirements and translate them into technical implementations.
• Document workflows, data schemas, and data definitions for internal use.
• Participate in code reviews, team meetings, and training sessions to continuously improve your skills
  Requirements2\u20134 years of experience working with data engineering or ETL tools (e.g., PySpark, SQL, Airflow).
  Solid understanding of SQL and basic experience with OLAP or data warehouse systems.
  Exposure to data lakes, preferably using Parquet format.
  Understanding of basic data modeling principles (e.g., star/snowflake schema).
  Good problem-solving skills and a willingness to learn and adapt.
  Ability to work effectively in a collaborative, fast-paced team environment.
  
  Preferred QualificationsExperience working with cloud platforms (e.g., AWS, Azure, or GCP).
  Exposure to low-code data tools or modular ETL frameworks.
  Interest or prior experience in the supply chain or logistics domain.
  Familiarity with dashboarding tools like Power BI, Looker, or Tableau.

Role: 

DBA / Data warehousing – OtherIndustry Type: 

Software ProductDepartment: 

Engineering – Software & QAEmployment Type: 

Full Time, PermanentRole Category: 

DBA / Data warehousing

EducationUG: 

Any GraduatePG: 

Any Postgraduate

Key Skills

Supply chainData modelingGCPSchemaCloudOLAPData warehousingAnalyticsSQLLogistics