JSW One Platforms - Data Engineer - ETL/BigQuery

Role Overview

• Build, maintain, and optimize data pipelines (batch and streaming, as needed) to - extract, transform, and load (ETL/ELT)- data from multiple, disparate source systems into a centralized data warehouse.
• Implement and manage data warehousing solutions using cloud-native technologies (e.g. on Google Cloud Platform - data warehouse like BigQuery, data ingestion/orchestration tools, etc.).
• Integrate data from diverse operational platforms (for different lines of business/departments) to create a unified, analytics-ready dataset.
• Perform data modeling and schema design to support reporting and analytics needs (e.g. star/snowflake schemas, dimensional models) and optimize storage and query performance.
• Ensure data quality, consistency, and reliability: implement validation/cleaning/transformation logic, monitor pipelines, handle issues, and maintain data governance and compliance processes.
• Work with business analysts, stakeholders and reporting/BI teams to understand business reporting requirements, translate them into data solutions, and deliver datasets for dashboards.
• Collaborate with BI/analytics/reporting tools and teams - support creation of dashboards and reports for various departments (e.g. sales performance, operations, executive dashboards, order management, customer service).
• Document data pipelines, data models, data flows, business logic and data definitions to help maintainability and team knowledge sharing.
• Help optimize data processing workflows for performance and cost-efficiency, including efficient querying and storage.
  

Required Qualifications & Skills

• Bachelor's degree in Computer Science, Engineering, or related technical discipline (or comparable experience).
• 2- 5 years of practical experience in data engineering, ETL/ELT pipelines, or related backend/data roles.
• Strong proficiency in - SQL- and a programming/scripting language such as - Python- (or similar).
• Experience with data warehousing platforms and cloud-based data infrastructure (preferably cloud-native warehouses or lakehouses).
• Solid understanding of data modeling, schema design (dimensional models), data normalization/denormalization, and data transformation concepts.
• Experience developing and maintaining ETL/ELT pipelines, working with both batch and (optionally) streaming datasets.
• Strong problem-solving skills, attention to detail, and commitment to data quality, consistency and reliability.
• Good communication and collaboration skills - able to liaise with non-technical stakeholders (business analysts, operations, leadership), understand requirements, and translate them into technical solutions.