Lead Assistant Manager-Data Engineering-Cloud Data Engineering
Chennai, Tamil Nadu, India
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign, develop and optimize data pipelines using PySpark and SQL
Implement and manage data warehousing solutions in Snowflake
Work with large-scale data processing in the Hadoop ecosystem
Ensure data quality, integrity and governance across data platforms
Monitor and troubleshoot pipeline performance and reliability
From the employer’s posting
Design, develop, and optimize robust data pipelines using PySpark and SQL.
Implement and manage data warehousing solutions using Snowflake.
Work with large-scale data processing frameworks within the Hadoop ecosystem.
Ensure data quality, integrity, and governance across all data platforms.
Monitor and troubleshoot data pipeline performance and reliability.
What you’ll bring
All qualificationsCore experience
- 5+ years of experience in data engineering or related roles
- Hands-on Snowflake: data modeling, performance tuning, security
- PySpark for distributed data processing
- Solid understanding of Hadoop ecosystem (HDFS, Hive, Spark)
- Advanced SQL skills for data manipulation and analysis
Qualification wording
5+ years of experience in data engineering or related roles.
Strong hands-on experience with Snowflake including data modeling, performance tuning, and security.
Knowledge in PySpark for distributed data processing.
Solid understanding of Hadoop ecosystem (HDFS, Hive, Spark, etc.).
Advanced SQL skills for data manipulation and analysis.
Tools in this posting
- SQL
- AWS
- Azure
- dbt
- GCP
- Hadoop
- Hive
- Snowflake
- Airflow
- PySpark
Source — Tool mentions in context
- 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. - Design, develop, and optimize robust data pipelines using PySpark and SQL.
- 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. - Design, develop, and optimize robust data pipelines using PySpark and SQL. - Implement and manage data warehousing solutions using Snowflake.
- Solid understanding of Hadoop ecosystem (HDFS, Hive, Spark, etc.). - Advanced SQL skills for data manipulation and analysis. - Experience with ETL tools and orchestration frameworks (e.g., Airflow, DBT).
- Experience with ETL tools and orchestration frameworks (e.g., Airflow, DBT). - Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus. - Excellent problem-solving and communication skills.
- Advanced SQL skills for data manipulation and analysis. - Experience with ETL tools and orchestration frameworks (e.g., Airflow, DBT). - Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.
- Implement and manage data warehousing solutions using Snowflake. - Work with large-scale data processing frameworks within the Hadoop ecosystem. - Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
- Knowledge in PySpark for distributed data processing. - Solid understanding of Hadoop ecosystem (HDFS, Hive, Spark, etc.). - Advanced SQL skills for data manipulation and analysis.
- Design, develop, and optimize robust data pipelines using PySpark and SQL. - Implement and manage data warehousing solutions using Snowflake. - Work with large-scale data processing frameworks within the Hadoop ecosystem.
- 5+ years of experience in data engineering or related roles. - Strong hands-on experience with Snowflake including data modeling, performance tuning, and security. - Knowledge in PySpark for distributed data processing.
- Strong hands-on experience with Snowflake including data modeling, performance tuning, and security. - Knowledge in PySpark for distributed data processing. - Solid understanding of Hadoop ecosystem (HDFS, Hive, Spark, etc.).
Posting record
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- Live
- First seen by us
- Aug 12, 2026 · 78 days ago
- Recorded sightings
- 331
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Oct 23, 2025
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
- 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.
- Design, develop, and optimize robust data pipelines using PySpark and SQL.
- Implement and manage data warehousing solutions using Snowflake.
- Work with large-scale data processing frameworks within the Hadoop ecosystem.
- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
- Ensure data quality, integrity, and governance across all data platforms.
- Monitor and troubleshoot data pipeline performance and reliability.
- Automate data workflows and implement best practices for data engineering.
- 5+ years of experience in data engineering or related roles.
- Strong hands-on experience with Snowflake including data modeling, performance tuning, and security.
- Knowledge in PySpark for distributed data processing.
- Solid understanding of Hadoop ecosystem (HDFS, Hive, Spark, etc.).
- Advanced SQL skills for data manipulation and analysis.
- Experience with ETL tools and orchestration frameworks (e.g., Airflow, DBT).
- Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.
- Excellent problem-solving and communication skills.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Chennai, Tamil Nadu, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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