Company
Technology
DataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer. Skills: Data Engineering, ETL/ELT, Microsoft Fabric, Data Modeling. Design ETL/ELT pipelines. Build ETL/ELT pipelines”
Industry & Context.
Problem solve; Root cause analysis
What They're Looking For.
Must Have
3+ years of hands-on experience in data engineering, Understanding of ETL/ELT concepts, Practical experience using SQL, Practical experience using Spark, Practical experience using Python, Practical experience using other programming languages, Microsoft Fabric experience, Dataflow Gen2 experience, Data Factory pipelines experience, Fabric Lakehouse experience, Fabric Warehouse experience, Demonstrated experience designing dimensional models, Demonstrated experience maintaining dimensional models, Star schemas with dimension and fact tables experience, Proven ability to normalize datasets, Proven ability to standardize datasets, Proven ability to join datasets, Proven ability to aggregate datasets, Experience supporting Power BI, Experience building API-based integrations, Working knowledge of MCPs, Working knowledge of authentication methods, Working knowledge of REST, Working knowledge of JSON, Working knowledge of webhooks, Ability to identify performance optimization opportunities, Ability to identify automation opportunities, Ability to identify cost efficiency opportunities, Ability to multi-task, Ability to problem solve, Ability to take ownership of work, Organizational skills, Documentation skills, Analytical skills
Nice to Have
Experience with Microsoft Dynamics NAV, Experience with Business Central, Experience with QuickBooks, Experience with Salesforce Commerce Cloud, Experience with Shopify, Experience with Amazon marketplaces, Experience with advertising data
What You'll Do.
Design ETL/ELT pipelines
Build ETL/ELT pipelines
Maintain ETL/ELT pipelines
Collaborate with Data Engineers
Collaborate with Developers
Deliver data solutions
Ingest data from source systems
Engineer dimensional models
Maintain dimensional models
Identify missing data
Identify incomplete data
Identify inaccurate data
Perform root cause analysis
Optimize data transformations
Optimize query performance
Optimize warehouse design
Prepare data architecture documentation
Maintain data architecture documentation
Prepare pipeline documentation
Maintain pipeline documentation
Prepare system diagrams
Maintain system diagrams
Assist building roadmaps
Identify opportunities to improve reporting enablement
Identify opportunities for automation
Identify opportunities for analytical capabilities
Perform ad hoc project work
How You'll Work.
Team & Collaboration
Collaborate with other Data Engineers; Collaborate with Developers; Collaborate with analysts; Collaborate with business stakeholders
Process & Methodology
Roadmap planning
Full Job Description
## 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 understandin
Applying for this Data Engineer role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Lever
- Lever uses a streamlined one-page form — apply in under 5 minutes.
- LinkedIn import works well; review parsed data before submitting.
- The cover letter field is optional but visible to reviewers — use it to differentiate.
- Referral codes from employees can significantly boost visibility of your application.
ANONYMOUS · UNFILTERED
What do employees actually say about this company?
Real rants from real employees. Read before you apply.