Senior Data Engineer- Snowflake

Parkar Global Technologies; Pune District; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Parkar Global Technologies in Pune invites an experienced Senior Data Engineer to design, develop, and maintain scalable data pipelines and modern data platforms. You will work closely with Data Architects, Analytics teams, and business stakeholders to deliver reliable data solutions using Snowflake, SQL, dbt, and Matillion, across Azure, AWS, and GCP environments.

You will optimize data ingestion, implement data quality checks, and mentor junior engineers in an Agile setting to ensure scalable,

Qualifications

• 6–8 years of experience in Data Engineering.
• Proficiency in Snowflake, SQL, dbt, and Matillion.
• Strong ETL/ELT pipeline development and data transformation skills.
• Solid understanding of data warehousing, data lakes, and dimensional modelling.
• Experience with Azure, AWS, or GCP.
• Knowledge of Git and CI/CD practices.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines for batch and near-real-time processing.
• Build and optimize Snowflake workloads and data platforms.
• Create data ingestion pipelines from databases, APIs, files and other sources.
• Implement data quality checks, validation, and monitoring.
• Collaborate with Data Architects and stakeholders to translate business needs into technical solutions.
• Participate in Agile/Scrum ceremonies and mentor junior engineers.

Skills

Snowflake

SQL

dbt

Matillion

ETL/ELT pipelines

Data warehousing

Cloud platforms

Git & CI/CD

Analytics

Job description

Job Summary

We are looking for an experienced Senior Data Engineer with 68 years of experience in designing, developing, and maintaining scalable data pipelines and modern data platforms.
The ideal candidate should have strong hands-on experience with Snowflake, SQL, ETL/ELT pipelines, cloud data platforms, data warehousing, and data integration. The candidate will work closely with Data Architects, Data Engineers, Analytics teams, and business stakeholders to build reliable, scalable, and high-quality data solutions.
Experience working with cloud platforms such as Azure/AWS/GCP and modern data engineering tools will be an added advantage.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines for batch and near-real-time data processing.Develop and optimize complex SQL queries, stored procedures, views, and data transformation logic.
• Build and maintain data solutions using Snowflake and modern cloud data platforms.
• Develop data ingestion pipelines to integrate data from databases, APIs, files,and other enterprise data sources.
• Implement data transformation, cleansing, validation, and enrichment processes.
• Design and maintain data warehouse and data lake solutions following industry best practices.
• Optimize Snowflake workloads, including query performance, data storage, compute usage, and resource utilization.
• Implement data quality checks and monitoring mechanisms to ensure accuracy and reliability of data pipelines.
• Troubleshoot pipeline failures, data issues, and performance bottlenecks and provide timely resolutions.
• Collaborate with Data Architects and stakeholders to understand business requirements and translate them into scalable technical solutions.
• Implement appropriate error handling, logging, monitoring, and alerting across data pipelines.
• Follow best practices for data security, governance, access control, and data management.
• Participate in code reviews and contribute to improving development standards and engineering practices.
• Work in Agile/Scrum environments and contribute to estimation, planning, and delivery activities.
• Mentor junior data engineers and support knowledge sharing within the team.

Required Skills

• 6-8 years of experience in Data Engineering.
• Proficiency in Snowflake, SQL, dbt, and Matillion - mandatory.
• Strong hands-on experience in ETL/ELT pipeline development and data transformation.
• Good understanding of data warehousing, data lakes, and dimensional modelling.
• Experience with at least one cloud platform: Azure, AWS, or GCP.
• Experience with data quality, performance tuning, monitoring, and troubleshooting.
• Good understanding of Git and CI/CD practices.
• Strong analytical, problem-solving, and communication skills.