Data Engineering/Data Architecture

RAPSYS TECHNOLOGIES PTE LTD; Bengaluru; Remote; INR 4,200,000 - 6,200,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE LTD in Bengaluru seeks a seasoned Data Engineering/Architecture leader with 12+ years of experience to design and scale data platforms that power insights.

You will own end-to-end data pipelines, set governance, mentor teams, and drive adoption of AWS, Snowflake, Airflow and dbt across the org.

Qualifications

• 12+ years of experience in data engineering and/or data architecture.
• Expert in AWS and Snowflake.
• Advanced PySpark and Python skills; basic knowledge not sufficient.
• Hands-on architecture experience designing and implementing data systems.
• AWS architecture at an architect level, not just basic cloud exposure.

Responsibilities

• Architect robust data pipelines and scalable architectures.
• Drive end-to-end data engineering projects from conception to deployment.
• Ensure data quality, governance, and security best practices.
• Collaborate with cross-functional teams to understand business requirements.
• Optimize performance of existing systems for reliability and speed.
• Evaluate emerging technologies and recommend adoption where beneficial.

Skills

Data engineering

Data architecture

AWS

Snowflake

PySpark

Python

Architecture leadership

Parallel processing

Tools

Airflow

dbt

Job description

We are searching for a seasoned professional in Data Engineering and Data Architecture to lead our data initiatives. With at least 12 years of experience, you will design, implement, and optimize scalable data solutions that power business insights and innovation.

Location: Bangalore Urban, India
Work Mode: Work from anywhere
Role: Data Engineering/Data Architecture

What You'll Do:

• Architect robust data pipelines and scalable architectures
• Drive end-to-end data engineering projects from conception to deployment
• Ensure data quality, governance, and security best practices
• Collaborate with cross-functional teams to understand business requirements
• Optimize performance of existing systems for reliability and speed
• Evaluate emerging technologies and recommend adoption where beneficial

What We're Looking For:

• Minimum 12 years of experience in data engineering/data architecture
• Core Stack: AWS and Snowflake – expert level, plus Airflow and dbt
• PySpark & Python are mandatory: Both need to be at an advanced/expert level. Basic or average knowledge is not sufficient.
• Real architecture experience: The candidate should have hands-on experience designing and implementing data architecture, not just theoretical exposure.
• AWS architecture: AWS experience should be at an architect level, not just basic cloud exposure.
• Architecture mindset: This is a critical requirement. The candidate should be able to think through scalability, performance, parallel processing, metadata-driven approaches, etc.
• Problem-solving example: For the scenario of refreshing 50 tables in 10 minutes instead of 100 minutes, the candidate should be able to immediately think about parallel processing/concurrency and architectural optimization.
• Leadership expectation: The requirement is for someone who can lead from an architecture and technical perspective, rather than someone who needs to be groomed into an architect.