Principal Data Engineer

ICIMS; Hyderabad; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

iCIMS is hiring Data Engineers at multiple levels in Hyderabad to build the next generation of our Talent Cloud platform. You will design, implement, and optimize data pipelines, storage systems, and analytics infrastructure to power data-driven decisions and AI capabilities.

You will collaborate with engineers, data scientists, and product teams, providing technical direction, mentoring, and leadership on high-impact projects. The role emphasizes scalable systems, governance, and innovation.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
• 7+ years of experience building data pipelines and systems.
• Proficiency in Python; familiarity with Java.
• Strong SQL skills and experience with relational and non-relational databases (e.g., SQL Server, PostgreSQL, MySQL, MongoDB).
• Expertise with cloud platforms (AWS preferred) and data storage services (e.g., S3, Redshift).
• Expertise with streaming platforms (Kafka, AWS Kinesis) and event-driven architectures.
• Strong understanding of data modelling, warehousing, and schema design principles.
• Expertise with data transformation tools (dbt), BI platforms (Looker), and API development for data consumption.
• Knowledge of version control (Git), CI/CD pipelines, and security principles for data systems (encryption, IAM, compliance frameworks).
• Expertise with user behaviour tracking platforms (Snowplow, Google Analytics) is a plus.
• Strong analytical and problem-solving skills with intellectual curiosity.
• Strong communication and collaboration skills across both technical and non-technical teams.
• Demonstrated experience in mentoring engineers, leading technical projects, or driving architectural decisions.

Responsibilities

• Lead a team of data engineers, providing technical direction, mentorship, and performance management
• Design, develop, and maintain scalable data pipelines to collect, process, and store data from multiple sources
• Build and optimise data infrastructure to support analytics, reporting, and AI/ML workloads at scale
• Implement event sourcing and streaming architectures using platforms (e.g., Kafka, AWS Kinesis) for real-time data processing
• Apply data governance, security principles, and compliance frameworks to ensure data quality and regulatory adherence
• Collaborate with data scientists, software engineers, and product teams to deliver reliable data solutions
• Troubleshoot and resolve data-related issues whilst maintaining data quality and integrity
• Contribute to best practices, frameworks, and tools for data engineering excellence
• Drive improvements in data engineering practices and data architecture
• Mentor data engineers and provide technical leadership on projects

Skills

Data pipeline design

Team leadership

Mentorship

Python

SQL

AWS

Kafka

Kinesis

dbt

Looker

API development

Git & CI/CD

Data governance

Analytics

Communication

Data engineering

Education

Bachelor's degree in Computer Science, Engineering, Data Science, or related field

Tools

Python

Java

SQL

AWS

Kafka

Kinesis

dbt

Looker

Git

CI/CD

Snowplow

Google Analytics

Job description

At iCIMS, we're redefining how people connect with opportunity through intelligent, human-centred technology. We're growing rapidly and are seeking Data Engineers at multiple levels of experience - from experienced to highly experienced professionals - to build the next generation of our Talent Cloud platform through scalable data pipelines, storage systems, and analytics infrastructure that power our data-driven decision-making and AI capabilities.

At iCIMS, we're redefining how people connect with opportunity through intelligent, human-centred technology. We're growing rapidly and are seeking Data Engineers at multiple levels of experience - from experienced to highly experienced professionals - to build the next generation of our Talent Cloud platform through scalable data pipelines, storage systems, and analytics infrastructure that power our data-driven decision-making and AI capabilities.

You’ll design, build, and optimise data infrastructure that supports analytics, business intelligence, and product development, working with software engineers, data scientists, and product experts and providing technical leadership on projects in a culture that values innovation, ownership, and continuous learning.

Responsibilities

• Lead a team of data engineers, providing technical direction, mentorship, and performance management
• Design, develop, and maintain scalable data pipelines to collect, process, and store data from multiple sources
• Build and optimise data infrastructure to support analytics, reporting, and AI/ML workloads at scale
• Implement event sourcing and streaming architectures using platforms (e.g., Kafka, AWS Kinesis) for real-time data processing
• Apply data governance, security principles, and compliance frameworks to ensure data quality and regulatory adherence
• Collaborate with data scientists, software engineers, and product teams to deliver reliable data solutions
• Troubleshoot and resolve data-related issues whilst maintaining data quality and integrity
• Contribute to best practices, frameworks, and tools for data engineering excellence
• Drive improvements in data engineering practices and data architecture
• Mentor data engineers and provide technical leadership on projects

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience)
• 7+ years of experience building data pipelines and systems
• Proficiency in Python; familiarity with Java
• Strong SQL skills and experience with relational and non-relational databases (e.g., SQL Server, PostgreSQL, MySQL, MongoDB)
• Expertise with cloud platforms (AWS preferred) and data storage services (e.g., S3, Redshift)
• Expertise with streaming platforms (e.g., Kafka, AWS Kinesis) and event-driven architectures
• Strong understanding of data modelling, warehousing, and schema design principles
• Expertise with data transformation tools (e.g., dbt), BI platforms (e.g., Looker), and API development for data consumption
• Knowledge of version control (Git), CI/CD pipelines, and security principles for data systems (encryption, IAM, compliance frameworks)
• Expertise with user behaviour tracking platforms (e.g., Snowplow, Google Analytics) is a plus
• Strong analytical and problem-solving skills with intellectual curiosity
• Strong communication and collaboration skills across both technical and non-technical teams
• Demonstrated experience in mentoring engineers, leading technical projects, or driving architectural decisions