We are looking for a highly experienced Data Engineer with strong hands-on expertise in Azure Databricks, PySpark, Python, dbt, and Snowflake.

Mandatory Technical Skills.

The candidate MUST have strong hands-on experience in:.

Azure Databricks – Mandatory.

PySpark – Mandatory.

Python – Mandatory.

dbt – Mandatory.

Snowflake – Mandatory.

Key Responsibilities.

Design, develop, and maintain scalable data engineering solutions using Azure Databricks and PySpark.

Develop robust and reusable data pipelines using Python and PySpark.

Build and optimize ETL/ELT pipelines for large-scale data processing.

Develop, maintain, and manage data transformation workflows using dbt.

Work extensively with Snowflake for data storage, transformation, optimization, and analytics workloads.

Integrate data from multiple source systems into Azure/Snowflake data platforms.

Develop complex SQL queries, stored procedures, data transformations, and performance-optimized data models.

Implement data quality, validation, reconciliation, and error-handling mechanisms.

Optimize Databricks jobs, Spark workloads, PySpark code, and Snowflake queries for performance and cost.

Design scalable batch and, where required, near-real-time data pipelines.

Troubleshoot production data pipeline failures and resolve technical issues.

Follow coding standards, CI/CD practices, version control, and deployment best practices.

Collaborate with architects, business stakeholders, and other engineering teams to deliver reliable data solutions.

Technical Requirements.

Azure Databricks.

Strong hands-on experience with Azure Databricks.





Experience developing and deploying Databricks notebooks and jobs.

Solid understanding of Spark architecture and distributed data processing.

Experience with performance tuning and optimization.

PySpark.

Strong hands-on experience developing PySpark applications.

Excellent understanding of DataFrames, transformations, actions, joins, partitioning, caching, and optimization.

Experience handling large-volume datasets.

Python.

Strong programming skills in Python.

Experience developing reusable, production-grade Python code for data engineering.

Strong understanding of exception handling, modular programming, and debugging.

dbt.

Hands-on experience with dbt development.

Experience building data transformation models, tests, documentation, and dependencies.

Strong understanding of ELT and modern data transformation frameworks.

Snowflake.

Strong hands-on experience with Snowflake.

Experience with data loading, transformation, warehouse optimization, and performance tuning.

Strong SQL skills.

Experience designing scalable Snowflake data models.

Additional Requirements.

Strong understanding of Data Warehousing and ETL/ELT concepts.

Strong SQL and data modeling skills.

Experience working with large-scale enterprise data platforms.

Good understanding of data quality and data governance practices.

Experience with Agile/Scrum development methodologies.

Strong analytical, troubleshooting, and problem-solving skills.

Excellent communication and collaboration skills

Interested candidates can share their updated CV at:

[email protected]

Pay: ₹50,000.00 - ₹100,000.00 per month

Benefits

- Provident Fund

Work Location: In person

📌 Senior Data Engineer (experience 6-10yrs) (Pune)
🏢 ZecData Technology
📍 Pune