Senior Data Engineer

Kayavlon Impex Pvt. Ltd; Bengaluru; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

Kayavlon Impex Pvt. Ltd in Bengaluru is seeking a Senior Data Engineer to develop and maintain scalable data pipelines, optimizing cloud data infrastructure.

This role requires strong expertise in data engineering frameworks and an ability to work collaboratively with various teams. Candidates should have a Bachelor’s degree in a related field and over 4 years of relevant experience. A proactive attitude with excellent problem-solving skills is essential.

Qualifications

• 4+ years of experience in data engineering or a similar role.
• Hands-on experience with ETL processes and integrations.
• Strong understanding of data governance principles and quality frameworks.

Responsibilities

• Develop and maintain scalable data pipelines.
• Collaborate with teams to understand data requirements.
• Monitor and troubleshoot data pipeline performance issues.

Skills

Experience in data engineering

Building and maintaining data pipelines

Programming languages (Python, SQL, Scala)

Cloud data platforms (Snowflake, Azure)

Data modelling principles

Problem-solving skills

Excellent communication skills

Education

Bachelor’s degree in Computer Science or related field

Tools

Snowflake

Apache Spark

Docker

Kubernetes

Git

Job description

As a Senior Data Engineer , you will play a key role in the development and maintenance of the

organization's data infrastructure. Working within a multi -disciplined team led by the Manager Data

Engineer ing , you will focus on building and optimizing scalable data pipelines and supporting the delivery of

high -quality, reliable data solutions.

This is an exciting opportunity to contribute to a dynamic and innovative environment, where your work will

directly impact the organization's ability to harness data for analytics, reporting, and decision -making.

THE GIG

As a Data Engineer , you will:

• Develop and maintain scalable data pipelines to support operational and analytical needs.
• Collaborate with data scientists, analysts, and business teams to understand data requirements and deliver solutions that align with organizational goals.
• Optimize and maintain cloud -based data infrastructure (e.g., Snowflake, Azure) for performance and cost -efficiency.
• Ensure the integrity, reliability, and security of data through robust testing and validation practices.
• Support the implementation of data governance practices, working closely with the Data QA Specialist and Data Governance Lead.
• Monitor and troubleshoot data pipeline performance issues, proactively resolving bottlenecks.
• Contribute to the design and implementation of data models and schemas that meet business requirements.
• Stay updated on emerging technologies and best practices, recommending improvements to existing processes and tools.

THE STUFF THAT SETS YOU APART

Must -Have Experience:

• 4 + years of experience in data engineering or a similar role.
• Hands -on experience building and maintaining data pipelines, ETL processes, and integrations.
• Proficiency in programming languages commonly used in data engineering (e.g., Python, SQL, Scala).
• Experience with cloud data platforms such as Snowflake or Azure.
• Solid understanding of data modelling principles and database management systems.

Technical Skills:

• Knowledge of big data frameworks and processing tools (e.g., Snowflake, Airflow, dbt, Apache Spark, Hadoop).
• Familiarity with DevOps practices, including CI/CD pipelines and version control systems (e.g., Git).
• Understanding of data governance principles, quality frameworks, and security best practices.
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus.

Soft Skills:

• Strong problem -solving skills with attention to detail.
• Excellent communication and collaboration skills, with the ability to work effectively within a team.
• A proactive attitude, with a willingness to learn and take ownership of tasks.

Education:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Relevant certifications in data engineering or cloud technologies are a plus.

Nice to Have:

• Experience in the retail or fashion industry, with exposure to its data and analytics challenges.
• Familiarity with real -time data processing and streaming technologies.
• Knowledge of DataOps principles and practices.