The Role:Must be located inFaridabador Delhi area
The Business Intelligence Team at PopSockets is a group of talented and agile professionals looking to add an experienced Data Engineer to our team as we continue growing globally. This role will focus on building and maintaining enterprise data warehouse solutions in Microsoft Fabric, with primary responsibility for designing, troubleshooting, and optimizing ETL/ELT processes that move data from disparate source systems into report and AI ready dimensional models. Working closely alongside US and India counterparts, this position will build and orchestrate pipelines in Fabric using Dataflow Gen2, Data Factory pipelines, and related Fabric capabilities to deliver reliable, scalable, and well-documented datasets for analytics and reporting used across the organization. The Data Engineer will be responsible for transforming raw operational data into high-quality star schemas with clearly defined dimension and fact tables that support Power BI and broader business intelligence needs. A successful candidate can manage competing priorities in a fast-paced environment while maintaining a high degree of organization and attention to detail. Additionally, they should be comfortable working within a global company that utilizes multiple ERP systems, eCommerce tools, marketplace APIs (including but not limited to Amazon Vendor and Seller Central), and Ad platforms. We are looking for an individual with a positive attitude who wants to grow their skill set at a dynamic company that values collaboration and hard work. This position reports to our Business Intelligence Lead in the US.
Responsibilities:

Design, build, and maintain enterprise ETL/ELT pipelines in Microsoft Fabric using Dataflow Gen2, Data Factory pipelines, and other Fabric-native tools

Collaborate closely with other Data Engineers and Developers in India to deliver scalable, well-orchestrated data solutions that support a global business

Ingest data from new and existing source systems into Microsoft Fabric using a combination of out-of-the-box connectors, APIs, and custom integration approaches

Transform and standardize disparate datasets into report-ready tables optimized for Power BI and downstream analytics use cases

Engineer and maintain dimensional models, including star schemas with fact and dimension tables,



to support enterprise reporting and analytical scalability

Collaborate with analysts and business stakeholders to understand data requirements and translate them into robust warehouse and semantic-ready data structures

Create and monitor jobs, alerts, and data quality checks to identify missing, incomplete, or inaccurate data and perform root cause analysis to resolve issues

Optimize data transformations, query performance, and warehouse design to improve reliability, efficiency, and cost management

Prepare and maintain data architecture documentation, pipeline documentation, system diagrams, and ERDs to clearly communicate lineage and transformation logic

Assist in building roadmaps for new data sources, warehouse enhancements, and process automation opportunities within the Fabric ecosystem

Identify opportunities to improve reporting enablement, automation, and analytical capabilities across the business

Other duties as assigned, including ad hoc project work
Requirements:

Bachelor's degree in Business Analytics, Computer Science and Engineering, Data Science, Information Systems, or another quantitatively rigorous discipline

3+ years of hands-on experience in data engineering, enterprise data warehousing, data modeling, or related disciplines

Strong understanding of ETL/ELT concepts, with practical experience using SQL, Spark, Python, and other programming languages

Hands-on experience with Microsoft Fabric, including Dataflow Gen2, Data Factory pipelines, and Fabric Lakehouse and Warehouse

Demonstrated experience designing and maintaining dimensional models, including star schemas with dimension and fact tables

Proven ability to normalize, standardize, join, and aggregate disparate raw datasets into report-ready tables at multiple levels of granularity

Experience supporting Power BI or similar BI platforms with analytics-ready datasets and semantic-friendly structures





Consistently leveraging AI to improve efficiency and processes with a desire to build data foundations that support the company's AI initiatives

Experience building and maintaining API-based integrations, with working knowledge of MCPs, authentication methods, and common integration patterns such as REST, JSON, and webhooks

Ability to identify opportunities for performance optimization, automation, and cost efficiency across data pipelines and warehouse processes

Ability to multi-task, problem solve, and take ownership of work in a quick-paced, high-growth setting

Must be detail oriented with strong organizational, documentation, and analytical skills

Strong work ethic, initiative, and a collaborative mindset with a positive attitude

Experience with Microsoft Dynamics NAV/Business Central, QuickBooks, Salesforce Commerce Cloud, Shopify, Amazon marketplaces, and advertising data is a plus
PopSockets is dedicated to the practice of equal opportunity employment. We prohibit unlawful discrimination against applicants and employees on the basis of age, race, sex, sexual orientation, gender identity, religion, national origin, disability, military status, genetic information, color, creed, ancestry, or any other status protected by applicable federal, state or local law. This prohibition includes unlawful harassment based on any of these protected classes. Unlawful harassment includes verbal or physical conduct which has the purpose or effect of interfering with an individual's work performance, or creating an intimidating, hostile, offensive, unsafe or otherwise non-welcoming work environment. This policy applies to all employees, including managers, supervisors, co-workers; and non-employees such as customers, clients, vendors, consultants, etc.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

📌 Data Engineer (India)
🏢 PopSockets
📍 India