Data Engineer - Data build tool

Hiring Data Engineers with data build tool experience for big4 firm in Gurgaon location.

Data Engineer – dbt Cloud & Airflow

Role Overview

We are looking for an experienced

Data Engineer

with strong hands-on expertise in

dbt Cloud and Apache Airflow

to design, develop, and maintain scalable data transformation and orchestration solutions. The ideal candidate should have practical experience working with

GCP BigQuery

and exposure to the

Financial Services (FS) domain

.

The role requires strong problem-solving skills and the ability to design solutions for real-world data engineering challenges, with a focus on

data quality, orchestration, scalability, maintainability, and reliable data pipelines

.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using

dbt Cloud and Apache Airflow

.

• Implement complex data transformation workflows using

dbt

.

• Develop and maintain

dbt Macros, Snapshots, Tests, Hooks, and Seeds

based on project requirements.

• Design and implement

Airflow DAGs

for efficient data orchestration and dependency management.

• Work with

Airflow architecture, Sensors, Operators, and orchestration patterns

.

• Implement

Airflow Dynamic Task Mapping

to improve scalability and pipeline efficiency.

• Work with

GCP BigQuery

for data processing, transformation, storage, and analytics.

• Implement data quality and validation frameworks using

dbt tests and other validation mechanisms

.

• Handle

Slowly Changing Dimensions (SCD Type 2)

and historical data tracking.

• Develop strategies for handling

late-arriving and out-of-sequence data

.

• Define appropriate

dbt implementation strategies

based on project architecture and business requirements.

• Troubleshoot complex data pipeline issues and identify effective solutions.
• Collaborate with business and technical stakeholders to understand requirements and translate them into robust data solutions.
• Ensure data pipelines are scalable, maintainable, reliable, and optimized for performance.
• Participate in solution design, architecture discussions, and technical decision-making.
• Contribute to production support, monitoring, troubleshooting, and continuous improvement of data engineering processes.

Good to Have

• Experience in the

Financial Services (FS) domain

.

• Experience in

Investment Management

or related financial domains.

• Experience working with large-scale data platforms and enterprise data environments.
• Exposure to cloud-based data engineering architecture and best practices.

Preferred Domain Experience

Candidates with experience in

Financial Services

, particularly

Investment Management

, will be preferred. However, Investment Management experience is

desirable and not mandatory

.

• Experience in the Financial Services (FS) domain.
• Experience in Investment Management or related financial domains.
• Experience working with large-scale data platforms and enterprise data environments.
• Exposure to cloud-based data engineering architecture and best practices.