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Data Engineer

PopSockets Open · verified Oct 24, 2026
Hybrid India Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at PopSockets. India · full-time.

Pay not stated Data Engineer salary

RoleData Engineering
SeniorityMid-level
LocationIndia
WorkplaceHybrid
EmploymentFull-time
PostedJun 3, 2026 · 4mo ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build and tune Microsoft Fabric pipelines that move data from source systems into reporting and AI-ready models
  • Connect new and existing systems to Fabric through connectors, APIs and custom integrations
  • Shape raw data into standardized Power BI tables and star schemas with fact and dimension tables
  • Work with engineers, developers, analysts and stakeholders to turn data needs into warehouse structures
  • Monitor data jobs and quality checks, investigate faulty data, improve performance, and document pipeline logic

What you bring

  • At least three years in data engineering, enterprise warehousing, data modeling or a related discipline
  • A bachelor's degree in a quantitative field such as computer science, data science or business analytics
  • Practical SQL, Spark and Python skills, plus hands-on use of Fabric, Dataflow Gen2 and Data Factory pipelines
  • Experience designing dimensional models and preparing varied raw data for reporting at different levels of detail
  • You can build API integrations and work with REST, JSON, webhooks and authentication methods

Who this fits

This role suits a hands-on data engineer comfortable balancing priorities, documenting work, and collaborating with teams in India and the US. You must be based in the Faridabad or Delhi area and work in a hybrid arrangement. It reports to a US-based Business Intelligence Lead.

From the employer

The Role: Must be located in Faridabad or 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 fast-paced, high-growth environment

    • 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.
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.