Data Pipeline Architect

About Client : -

Our client is a French multinational information technology (IT) services and consulting company, headquartered in Paris, France. Founded in 1967, It has been a leader in business transformation for over 50 years, leveraging technology to address a wide range of business needs, from strategy and design to managing operations.

The company is committed to unleashing human energy through technology for an inclusive and sustainable future, helping organizations accelerate their transition to a digital and sustainable world.

They provide a variety of services, including consulting, technology, professional, and outsourcing services.

Job Details : -

location : Pune

Mode Of Work : Hybrid

Notice Period : Immediate Joiners

Experience : 8-10 yrs

Type Of Hire : Contract to Hire

Primary Skills : -

Detailed JD :

"Data Engineer with deep expertise in DBT (Data Build Tool), Snowflake, and PL / SQL to join our growing data team. Person will be responsible for designing, developing, and maintaining robust data transformation pipelines that support business intelligence, analytics, and data science initiatives.

Key Responsibilities :

Design and implement scalable data models and transformation pipelines using DBT on Snowflake .

Write efficient and maintainable PL / SQL code for complex data processing and transformation tasks.

Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality solutions.

Optimize Snowflake performance through query tuning, clustering, and resource management.

Ensure data quality, integrity, and governance through testing, documentation, and monitoring.

Participate in code reviews, architecture discussions, and continuous improvement initiatives.

Maintain and enhance CI / CD pipelines for DBT projects.

Required Qualifications :

8+ years of experience in data engineering or a related field.

Strong hands-on experience with DBT (modular SQL development, testing, documentation).

Proficiency in Snowflake (data warehousing, performance tuning, security).

Advanced knowledge of PL / SQL and experience with stored procedures, functions, and packages.

Solid understanding of data modeling concepts (star / snowflake schemas, normalization).

Experience with version control systems (e.G., Git ) and CI / CD practices.

Familiarity with orchestration tools (e.G., Airflow, dbt Cloud, Prefect ) is a plus."