Time since we first saw it
Day 45
Similar jobs usually come down between day 6 and day 54.
At Brillio-2, jobs usually come down by about day 25.
From 11,418 similar postings that came down, and 58 of Brillio-2’s. Coming down is not always a hire.
Lead Data Engineer
Bangalore, Karnataka, India
Live, first seen by us 45 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDevelop, maintain and optimize dbt models, macros and tests for ETL/ELT pipelines
Administer Snowflake warehouses, including databases, schemas, roles and security
Design and maintain dbt models across Bronze, Silver and Gold layers
Implement and maintain CI/CD pipelines for data deployments
Troubleshoot production issues and perform root cause analysis
From the employer’s posting
Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines
Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations
Design, build, and maintain dbt models across Bronze → Silver → Gold layers for the assigned domain.
Implement and maintain CI/CD pipelines for automated deployment and release management of data solutions
Troubleshoot and resolve production issues, conducting thorough root cause analysis to minimize downtime and prevent recurrence
What you’ll bring
All qualificationsCore experience
- Expertise in developing and managing dbt models, macros, and tests
- Hands-on experience with Snowflake data warehousing, including Time Travel and Fail Safe features
- Strong understanding of ETL/ELT fundamentals and best practices
- Proficiency in Python for data engineering and automation tasks
Preferred experience
- Experience with modern data platform fundamentals and architecture
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field
- Expertise in optimizing large-scale data pipelines for performance and cost efficiency
- Familiarity with data governance and compliance best practices in cloud environments
Qualification wording
Expertise in developing and managing dbt models, macros, and tests
Hands-on experience with Snowflake data warehousing, including Time Travel and Fail Safe features
Strong understanding of ETL/ELT fundamentals and best practices
Proficiency in Python for data engineering and automation tasks
Experience with modern data platform fundamentals and architecture
Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field
Expertise in optimizing large-scale data pipelines for performance and cost efficiency
Familiarity with data governance and compliance best practices in cloud environments
Education & alternatives
Desired Qualifications: - Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field - Relevant industry certifications in AWS, Snowflake, or dbt are highly desirable
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 22, 202645 days ago
- Recorded sightings
- 100
- Last seen by us
- Nov 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Brillio-2 is hiring
46 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring has slowed
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- dbt
- S3
- Snowflake
Where the posting names them
- Strong understanding of ETL/ELT fundamentals and best practices - Proficiency in Python for data engineering and automation tasks - Administration of Snowflake warehouses, databases, schemas, and role-based security
- Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations to ensure robust data governance - Optimize complex SQL queries and warehouse performance, reducing processing times and improving storage utilization - Manage and integrate AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch to build and maintain reliable cloud data infrastructure
Required Skills: - Advanced proficiency in SQL (basic and advanced) - Expertise in developing and managing dbt models, macros, and tests
Job requirements Experience Range: 8- 10 years of experience in data engineering, with hands-on expertise in Snowflake, dbt, and AWS cloud services Key Responsibilities: - Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines
- Optimize complex SQL queries and warehouse performance, reducing processing times and improving storage utilization - Manage and integrate AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch to build and maintain reliable cloud data infrastructure - Implement and maintain CI/CD pipelines for automated deployment and release management of data solutions
- Administration of Snowflake warehouses, databases, schemas, and role-based security - Management of AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch - Implementation and maintenance of CI/CD pipelines for data deployments
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field - Relevant industry certifications in AWS, Snowflake, or dbt are highly desirable Employment type
Experience Range: 8- 10 years of experience in data engineering, with hands-on expertise in Snowflake, dbt, and AWS cloud services Key Responsibilities: - Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines - Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations to ensure robust data governance
- Collaborate closely with analytics, business intelligence, and engineering teams to deliver high-impact, scalable data solutions aligned with business objectives - Medallion modeling: Design, build, and maintain dbt models across Bronze → Silver → Gold layers for the assigned domain. - Governance alignment: Partner with the Data Governance team so models meet certification and quality-gate standards before promotion.
- Advanced proficiency in SQL (basic and advanced) - Expertise in developing and managing dbt models, macros, and tests - Hands-on experience with Snowflake data warehousing, including Time Travel and Fail Safe features
- Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines - Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations to ensure robust data governance - Optimize complex SQL queries and warehouse performance, reducing processing times and improving storage utilization
- Expertise in developing and managing dbt models, macros, and tests - Hands-on experience with Snowflake data warehousing, including Time Travel and Fail Safe features - Strong understanding of ETL/ELT fundamentals and best practices
- Proficiency in Python for data engineering and automation tasks - Administration of Snowflake warehouses, databases, schemas, and role-based security - Management of AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch
- Knowledge of infrastructure-as-code tools for cloud resource management - Exposure to advanced Snowflake features such as data sharing and secure data exchange Desired Qualifications:
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Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
Lead Data Engineer
Job requirements
- Develop, maintain, and optimize dbt models, macros, and tests to support scalable ETL/ELT data pipelines
- Administer and manage Snowflake data warehouses, including databases, schemas, roles, and security configurations to ensure robust data governance
- Optimize complex SQL queries and warehouse performance, reducing processing times and improving storage utilization
- Manage and integrate AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch to build and maintain reliable cloud data infrastructure
- Implement and maintain CI/CD pipelines for automated deployment and release management of data solutions
- Configure and monitor data quality checks, alerting systems, and performance monitoring to ensure high data reliability and integrity
- Troubleshoot and resolve production issues, conducting thorough root cause analysis to minimize downtime and prevent recurrence
- Collaborate closely with analytics, business intelligence, and engineering teams to deliver high-impact, scalable data solutions aligned with business objectives
- Medallion modeling: Design, build, and maintain dbt models across Bronze → Silver → Gold layers for the assigned domain.
- Governance alignment: Partner with the Data Governance team so models meet certification and quality-gate standards before promotion.
- Downstream support: Support data modeling for downstream analytics platform consumers (dashboards and data products)
- Troubleshooting & support: Diagnose and resolve pipeline issues; participate in on-call/support rotation as needed.
- Documentation: Document data lineage, model logic, and key technical decisions so the work is maintainable by the internal team.
- Maintain and Develop APIs
- Advanced proficiency in SQL (basic and advanced)
- Expertise in developing and managing dbt models, macros, and tests
- Hands-on experience with Snowflake data warehousing, including Time Travel and Fail Safe features
- Strong understanding of ETL/ELT fundamentals and best practices
- Proficiency in Python for data engineering and automation tasks
- Administration of Snowflake warehouses, databases, schemas, and role-based security
- Management of AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch
- Implementation and maintenance of CI/CD pipelines for data deployments
- Configuration of monitoring, alerting, and data quality checks in cloud data platforms
- Experience with modern data platform fundamentals and architecture
- Expertise in optimizing large-scale data pipelines for performance and cost efficiency
- Familiarity with data governance and compliance best practices in cloud environments
- Knowledge of infrastructure-as-code tools for cloud resource management
- Exposure to advanced Snowflake features such as data sharing and secure data exchange
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field
- Relevant industry certifications in AWS, Snowflake, or dbt are highly desirable
Experience Range: 8- 10 years of experience in data engineering, with hands-on expertise in Snowflake, dbt, and AWS cloud services Key Responsibilities:
Required Skills:
Preferred Skills:
Desired Qualifications:
Employment type
Employee
Source details
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- Location & working pattern
Bangalore, Karnataka, India
Working pattern and location restrictions need checking in the full posting.
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