This role is no longer listed.First Citizens India took the posting down on 19 Oct, so applying now won't reach anyone. It stays here for your saved list and any links you shared.
Lead Data Engineer - Snowflake and DBT
First Citizens India (company site, opens in a new tab)10+ yrsBengaluruOn-siteDirect career pageEst. 30–45 LPA
Posted 9h ago
Reach people at First Citizens India
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at First Citizens India you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and maintain enterprise-scale data platforms and data pipelines supporting the Enterprise Data Warehouse and related systems.
- Establish and optimize data integration frameworks, including performance tuning of complex data pipelines and SQL queries.
- Manage team deliverables, conduct design reviews, coordinate release management, and collaborate across global teams for timely delivery and incident resolution.
Minimum Requirements
- 10+ years experience in Data Engineering with strong expertise in Snowflake and enterprise data warehousing.
- Proven skills in ETL/ELT tools such as DBT, Qlik Replicate, Snowpark, and orchestration tools like Airflow.
- Technical proficiency in AWS cloud services (S3, Lambda, Glue, Step Function, CloudWatch) and scripting in Unix and Python.
- Work Experience Required: 10+ years in Data Engineering roles.
Ideal Candidate Profile
- Experienced leader capable of managing a team and coordinating cross-functional/global stakeholders in a hybrid work environment.
- Strong background in large-scale, cloud-based data platform design and migration from legacy systems.
- Technical depth in data architecture, modeling (relational, dimensional, Data Vault), and high-volume data pipeline performance optimization.