Lead Assistant Manager-Data Engineering-Cloud Data Engineering

1. The ideal candidate will have strong expertise in

Snowflake

,

Hadoop ecosystem

,

PySpark

, and

SQL

, and will play a key role in enabling data-driven decision-making across the organization.

1. Design, develop, and optimize robust data pipelines using PySpark and SQL.
2. Implement and manage data warehousing solutions using Snowflake.
3. Work with large-scale data processing frameworks within the Hadoop ecosystem.
4. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
5. Ensure data quality, integrity, and governance across all data platforms.
6. Monitor and troubleshoot data pipeline performance and reliability.
7. Automate data workflows and implement best practices for data engineering.

1. 5+ years of experience in data engineering or related roles.
2. Strong hands-on experience with

Snowflake

including data modeling, performance tuning, and security.
3. Knowledge in

PySpark

for distributed data processing.
4. Solid understanding of

Hadoop ecosystem

(HDFS, Hive, Spark, etc.).
5. Advanced SQL skills for data manipulation and analysis.
6. Experience with ETL tools and orchestration frameworks (e.g., Airflow, DBT).
7. Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.
8. Excellent problem-solving and communication skills.