Website:
nasugroup.com
Job details:
About the Role
We are looking for an experienced Data Engineer to design, develop, and manage scalable data platforms, pipelines, and data products. The role will focus on delivering trusted, governed, secure, and high-quality data solutions for analytics, AI/ML, reporting, and business operations.
The ideal candidate should have strong hands-on experience with Python, SQL, PySpark, Databricks, Azure Data Factory, Azure Synapse, ADLS, Snowflake, and modern cloud data engineering practices.
Key Responsibilities
Design and develop data ingestion, transformation, and integration pipelines.
Build scalable batch, streaming, and near real-time data processing solutions.
Develop and optimize Data Lake, Lakehouse, and Data Warehouse architectures.
Build reusable data models, curated datasets, and enterprise data products.
Implement data quality, governance, metadata, lineage, monitoring, and security controls.
Optimize data pipelines and platform performance for scalability and reliability.
Collaborate with Data Architects, Data Scientists, Analysts, and Business teams.
Troubleshoot production data issues and improve operational stability.
Implement automation and standardization across data engineering processes.
Follow CI/CD and DevOps practices for data platform development and deployment.
Support enterprise analytics and business use cases across multiple functions.
Mandatory Technical Skills
Programming & Data Processing
Strong SQL skills.
Strong hands-on experience with Python.
Experience with PySpark.
Knowledge of Scala and/or Java is preferred.
Databricks & Data Platforms
Strong experience with Databricks.
Hands-on experience with Delta Lake.
Experience developing scalable data pipelines and transformations.
Understanding of Lakehouse architecture.
Azure Technologies
Azure Data Factory (ADF)
Azure Synapse Analytics
Azure Data Lake Storage (ADLS)
Cloud Data Warehouse
Hands-on experience with Snowflake or equivalent cloud data platforms.
Data Modeling
Strong understanding of:
Star Schema
Snowflake Schema
Data Vault
Dimensional Data Modeling
DevOps & Engineering Practices
CI/CD
DevOps practices
Monitoring & Observability
Pipeline performance optimization
Production support and troubleshooting
Data Governance
Data Quality
Data Governance
Metadata Management
Data Lineage
Data Security
Preferred Experience
Experience working with large-scale enterprise data platforms.
Experience with batch and streaming data processing.
Exposure to manufacturing, pricing, prognostics, or commercial analytics.
Experience building reusable data products for analytics and business teams.
Experience working in Agile delivery environments.
Key Success Measures
Reliable, secure, and governed enterprise data delivery.
Improved scalability and performance of data platforms.
Reduction of manual effort through automation.
High-quality and reusable data products.
Improved adoption of enterprise data solutions.
Successful enablement of analytics and business use cases.
Candidate Profile
We are looking for a 6–8 year experienced Data Engineer with strong hands-on cloud data engineering expertise, particularly across Databricks, PySpark, Azure Data Factory, Azure Synapse, ADLS, Snowflake, SQL, and Python.
Location: Pune
Experience: 6–8 Years
Employment: Contract / Subcontract
Click on Apply to know more.
