Lead Data Engineer

First Citizens India; Bengaluru; Hybrid; INR 3,500,000 - 5,500,000; Full time

Job summary

First Citizens India seeks a Lead Data Engineer to lead the design and maintenance of large-scale data platforms and data lakes. You will build enterprise data pipelines, manage ETL/ELT processes, and coordinate release activities with global teams.

The role requires 10+ years of experience, strong SQL, and expertise in Snowflake and AWS. You will work in a hybrid setup, collaborating with stakeholders across the organization on data strategy and governance.

Qualifications

• 10+ years of experience designing and building Data Warehouse and Data Lakes.
• Knowledge of data warehouse principles and concepts.
• Technical expertise with large scale Data Warehousing databases (Oracle, Netezza, Teradata, SQL Server).
• Cloud-based data platform experience especially Snowflake and AWS.
• Expertise in design and development of complex data pipelines.
• Experience with ETL tools such as IBM DataStage, SSIS, SAP BO Data Services (BODS).
• Unix, Python or equivalent scripting language.
• Transform/ELT tools such as DBT, AWS Glue, Snowpark, etc.
• Strong SQL, stored procedures, and data integrity troubleshooting.
• Data modeling, data architecture knowledge, and data vault concepts.
• Control-M scheduling experience.

Responsibilities

• Lead the design, development, and maintenance of large-scale data platforms and data lakes.
• Build and optimize data pipelines for enterprise data through ETL/ELT processes.
• Guide delivery timelines and coordinate release management with multiple teams.
• Provide technical risk assessment and incident response support.
• Collaborate with Product Owners and global teams across time zones to deliver value.
• Drive automation and continuous improvement of data flows and processes.

Skills

Team Player

Communication

Problem Solving

Partnership & Collaboration

Attention to Detail

Leadership

Tools

Oracle

Netezza

Teradata

SQL Server

Snowflake

AWS

IBM DataStage

SSIS

SAP Business Objects Data Services

Python

DBT

Qlik Replicate

AWS Glue

Snowpark

Control-M

Gitlab CI/CD

Job description

• Lead the development and maintenance of large-scale data platforms, data lakes and cloud solutions.
• Responsible for designing and building data pipelines for enterprise data through ETL/ELT processes.

Position Title: Lead Data Engineer

Job Category: Manager

Role Type: Hybrid

About the Team:

The data engineering team is community of dedicated professionals committed to designing, building, and maintaining data platform solutions for the organization.

Impact

Enterprise data warehouse supports several critical business functions for the bank including Regulatory Reporting, Finance, Risk steering, and Customer 360. This role is vital for building and maintaining enterprise data platform, data processes, and to support business objectives. Our values — inclusivity, transparency, and excellence — drive everything we do. Join us and make a meaningful impact on the organization.

• Responsible for designing, building, and maintaining data platform that supports data integrations for Enterprise Data Warehouse, Operational Data Store or Data Marts etc. with appropriate data access, data security, data privacy and data governance.
• Establish enterprise-scale data integration procedures, data pipelines and frameworks across the data development life cycle. Suggest and implement appropriate technologies to deliver resilient, scalable, and future-proof data solutions.
• Create data ingestion pipelines in data warehouses and other large-scale data platforms.
• Creating scheduled as well as trigger-based ingestion patterns using scheduling tools.
• Create performance optimized DDLs for any row-based or columnar databases such as Oracle, Postgres, Netezza database per Logical Data Model.
• Performance tuning of complex data pipelines and SQL queries.
• Performs impact analysis of proposed changes on existing architecture, capabilities, system priorities, and technology solutions.
• Manage deliverables of developers, perform design reviews and coordinate release management activities.
• Estimate and provide timelines for project activities. Identify, document, and communicate technical risks, issues and alternative solutions discovered during project.
• Drive automation, identify inefficiencies, optimize processes and data flows, and recommend improvements.
• Use agile engineering practices and various data development technologies to rapidly develop and implement efficient data products.
• Collaborate with Product Owners to understand PI goals, PI planning, requirement clarification, and delivery coordination.
• Technical support for production incidents and failures
• Work with global technology teams across different time zones (primarily US) to deliver timely business value.

Skills and Qualification

Functional Skills:

• Team Player: Support peers, team, and department management.
• Communication: Excellent verbal, written, and interpersonal communication skills.
• Problem Solving: Excellent problem-solving skills, incident management, root cause analysis, and proactive solutions to improve quality.
• Partnership and Collaboration: Develop and maintain partnership with business and IT stakeholders
• Attention to Detail: Ensure accuracy and thoroughness in all tasks.

Technical/Business Skills:

• 10+ years of experience in designing and building Data Warehouse and Data lakes. Good knowledge of data warehouse principles, and concepts.
• Technical expertise working in large scale Data Warehousing applications and databases such as Oracle, Netezza, Teradata, and SQL Server.
• Cloud-based data platform experience especially Snowflake and AWS.
• Expertise in design and development of complex data pipelines
• Solutions using any industry leading ETL tools such as IBM Data Stage or SSIS or SAP Business Objects Data Services (BODS)
• Experience with Unix, Python or equivalent scripting language
• Basic knowledge of Transform/ELT tools such as DBT, Qlik Replicate, AWS Glue or Snowpark, etc.
• Expert in SQL, stored procedures and adept in tracing and resolving data integrity issues.
• Strong knowledge of data architecture, data design patterns, modeling
• Data Model: Expertise in Logical and Physical Data Model using Relational, Dimensional or Data Vault Modeling practices with high volume ETL/ELT processes.
• Good experience with scheduling tools such as Control-M
• Performance tuning of data pipelines and DB Objects to deliver optimal performance.
• Experience in Gitlab version control and CI/CD processes.
• Experience working in Financial Industry is a plus.

Relationships & Collaboration

• Reports to: Associate Director - Data Engineering
• Partners: Senior leaders and cross-functional teams
• Leads: A team of Data Engineering associates

Accessibility Needs

We are committed to providing an inclusive and accessible hiring process. If you require accommodations at any stage (e.g. application, interviews, onboarding) please let us know, and we will work with you to ensure a seamless experience.