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Shuru Technologies Private Limited

Senior Data Engineer

Shuru Technologies Private Limited

IT Services and IT Consulting · 51-200 employees

Yesterday
Remote data-engineer Senior (5-10 yrs) Full-time
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About the role

Build and maintain scalable data pipelines using Azure Databricks, PySpark, and SQL while developing Bronze, Silver, and Gold data layers. Collaborate with cross-functional teams to implement data validation, quality checks, and production-ready analytics solutions.

What they look for

Azure Databricks PySpark SQL Delta Lake Data Engineering Lakehouse Architecture Data Modeling Dimensional Modeling Data Quality Pipeline Monitoring Git CI/CD Data Governance Data Security Data Lineage

Requirements

Requires 5–8 years of data engineering experience with strong proficiency in Azure Databricks, PySpark, and SQL. Candidates must have a solid understanding of Lakehouse architecture, data modeling, and CI/CD practices.

Benefits

Challenging large-scale engineering and data projects Modern platform development Collaboration with experienced leadership Ownership of architecture and technical decisions Remote-first environment Career growth and leadership opportunities

Full description

This is a remote position.

Shuru is an AI-native technology and engineering company that partners with businesses to build and scale high-impact digital products, platforms, and AI-driven solutions. We work with fast-growing organizations across industries, helping them solve complex technology challenges through strong engineering, product, data, and AI capabilities.

Shuru is looking for a Senior Data Engineer to build scalable and reliable data pipelines for a global fintech engagement. This is a hands-on role focused on Azure Databricks, PySpark, SQL, and Delta Lake.

  • Build and maintain data pipelines using Azure Databricks, PySpark, and SQL.
  • Develop Bronze, Silver, and Gold data layers using Delta Lake.
  • Build and optimize data models for analytics and business use cases.
  • Implement data validation, testing, monitoring, and quality checks.
  • Troubleshoot pipeline and data quality issues.
  • Work closely with data leads, analysts, and engineering teams to deliver production-ready solutions.
  • Follow data governance, security, cataloging, and lineage standards.

Requirements

  • 5–8 years of Data Engineering experience.
  • Strong hands-on experience with Azure Databricks, PySpark, and SQL.
  • Experience with Delta Lake and Lakehouse architecture.
  • Strong understanding of data modelling and dimensional modelling.
  • Experience with data quality, testing, and pipeline monitoring.
  • Familiarity with Git and CI/CD.

Benefits

  • Work on challenging, large-scale engineering and data problems.
  • Build modern platforms using cutting-edge cloud and data technologies.
  • Work closely with experienced engineering, product, and technology leaders.
  • Opportunity to take ownership of architecture and key technical decisions.
  • Remote-first and collaborative work environment.
  • Strong opportunities for learning, leadership, and career growth.

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