Azure Data Engineer

Company Description SculptSoft is an AI software development company that turns bold ideas into intelligent, scalable, and future-ready digital products. With strong expertise in Artificial Intelligence, Generative AI, automation, and cloud, the team builds systems that streamline operations, personalize user experiences, and enable data-driven decisions. For over 13 years, SculptSoft has partnered with startups and enterprises across sectors such as Healthcare, Fintech, Education, Real Estate, E-Commerce, Manufacturing, Automobile, Mortgage, Travel & Hospitality, and Fire Safety. The company supports clients across the full product lifecycle—from discovery and design to development, deployment, and optimization—focusing on quality, speed, and measurable impact. With strategic teams in India and the USA, SculptSoft offers services in AI/ML, data engineering and analytics, web and mobile development, SaaS platforms, DevOps, and cloud (AWS, Azure, GCP).
Role Description The Azure Data Engineer is a full-time, on-site role based in Ahmedabad. This role is responsible for designing, building, and maintaining scalable data pipelines and solutions on Azure, ensuring reliable data ingestion, transformation, and storage for analytics and AI initiatives. Day-to-day tasks include developing and optimizing ETL processes, implementing data models, and configuring data warehouses and data lakes using Azure services such as Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure Storage. The Azure Data Engineer will collaborate closely with data scientists, analysts, and software engineers to deliver clean, well-structured datasets, improve data quality, and support reporting and business intelligence needs. The role also involves monitoring performance, troubleshooting data issues, enforcing data security and governance standards, and contributing to best practices and documentation.
Qualifications
Strong data engineering skills, including experience with Azure data services (e.g., Azure Data Factory, Azure Synapse, Azure Databricks, Azure SQL, Azure Data Lake).
Proficiency in data modeling and designing scalable schemas for analytical and operational workloads.
Hands-on experience with Extract Transform Load (ETL) pipelines, including building, scheduling, and optimizing batch and streaming data workflows.
Knowledge of data warehousing concepts and implementation, including star/snowflake schemas and dimensional modeling.
Ability to work with data analytics teams, enabling dashboards, reports, and self-service analytics through well-structured data sets.
Solid skills in SQL and at least one programming language commonly used in data engineering (such as Python or Scala).
Understanding of data security, governance, and compliance best practices in cloud environments.
Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field; relevant certifications in Azure

Work arrangement
No