Data Engineer IV

Chennai

Pay: Pay not listed
Work setting: Not stated
Employment: Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting

Apply at Pditechnologies

What you’ll work on

Full posting

Design and optimize scalable cloud data pipelines for analytics and reporting
Lead complex data integration solutions using AWS-native technologies
Design data models, ingestion frameworks, and transformation processes
Establish engineering standards and reusable frameworks
Mentor other data engineers through code reviews and knowledge sharing

From the employer’s posting

As a Data Engineer IV, you will serve as a senior technical contributor responsible for designing, developing, and optimizing scalable cloud-based data solutions that enable enterprise analytics, reporting, and business intelligence. You will lead the delivery of complex data integration initiatives, establish engineering best practices, and provide technical guidance to other engineers. This role requires a strong understanding of modern data engineering practices and a conceptual understanding of data architecture principles to design scalable, maintainable, and governed data solutions while partnering with business and technology teams to solve complex business problems.

Design, develop, and optimize scalable cloud-based data pipelines that support enterprise analytics, reporting, and business intelligence.

Lead the development of complex data integration solutions using AWS-native technologies

Design scalable data models, ingestion frameworks, and transformation processes

Establish and promote engineering standards, reusable frameworks, and best practices

Mentor and provide technical guidance to other data engineers through code reviews, knowledge sharing, and best practice adoption.

What you’ll bring

All qualifications

Core experience

Bachelor's degree in computer science, Information Technology, Engineering, or a related field, or equivalent practical experience.
8+ years of experience in data engineering, cloud data platforms, or related software engineering roles.
Practical experience with applying AI/ML techniques to data engineering problems, such as automated data quality checks, anomaly detection, or intelligent pipeline monitoring.
Practical experience developing semantic and contextual layers within a data lake house.
Strong understanding of dimensional modeling, data warehousing, data lakehouse concepts, Apache Iceberg, Parquet, and modern data engineering practices.
Experience integrating enterprise platforms such as Salesforce, NetSuite, and other SaaS applications.

Qualification wording

Bachelor's degree in computer science, Information Technology, Engineering, or a related field, or equivalent practical experience.

8+ years of experience in data engineering, cloud data platforms, or related software engineering roles.

Practical experience with applying AI/ML techniques to data engineering problems, such as automated data quality checks, anomaly detection, or intelligent pipeline monitoring.

Practical experience developing semantic and contextual layers within a data lake house.

Strong understanding of dimensional modeling, data warehousing, data lakehouse concepts, Apache Iceberg, Parquet, and modern data engineering practices.

Experience integrating enterprise platforms such as Salesforce, NetSuite, and other SaaS applications.

Education & alternatives

Qualifications - Bachelor's degree in computer science, Information Technology, Engineering, or a related field, or equivalent practical experience. - 8+ years of experience in data engineering, cloud data platforms, or related software engineering roles.

Tools in this posting

Python
SQL
AWS
Azure
Iceberg
Redshift
S3
Terraform
PySpark

Source

- Expert experience developing cloud-based data solutions using AWS technologies such as S3, Glue, Redshift, AppFlow, Lake Formation, Step Functions, and related services. - Advanced proficiency with SQL, Python, and PySpark for developing scalable ETL/ELT solutions. - Practical experience with applying AI/ML techniques to data engineering problems, such as automated data quality checks, anomaly detection, or intelligent pipeline monitoring.

- Design, develop, and optimize scalable cloud-based data pipelines that support enterprise analytics, reporting, and business intelligence. - Lead the development of complex data integration solutions using AWS-native technologies and modern data engineering practices. - Design scalable data models, ingestion frameworks, and transformation processes that support reliable, high-quality analytics.

- 8+ years of experience in data engineering, cloud data platforms, or related software engineering roles. - Expert experience developing cloud-based data solutions using AWS technologies such as S3, Glue, Redshift, AppFlow, Lake Formation, Step Functions, and related services. - Advanced proficiency with SQL, Python, and PySpark for developing scalable ETL/ELT solutions.

- Strong understanding of modern data engineering practices with conceptual knowledge of data architecture principles, including data modeling, governance, metadata management, and scalable cloud data platforms. - Experience with Infrastructure as Code (Terraform), Git, Azure DevOps, and CI/CD pipelines. - Demonstrated ability to mentor engineers, influence technical decisions, and drive engineering best practices without formal people leadership.

- Practical experience developing semantic and contextual layers within a data lake house. - Strong understanding of dimensional modeling, data warehousing, data lakehouse concepts, Apache Iceberg, Parquet, and modern data engineering practices. - Experience integrating enterprise platforms such as Salesforce, NetSuite, and other SaaS applications.

Posting record

Report an error

Status in our records: Live
First seen by us: Aug 2, 2026 · 87 days ago
Recorded sightings: 44
Last seen by us: Oct 29, 2026
Employer says posted: Jul 30, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

Have your resume and examples of relevant work ready.
Check the listed location, eligibility and core experience before starting.
Ask the employer about the pay range before committing time to the process.

Complete your application on jobs.lever.co. The employer’s form will show what is required.

Already applied? Track this application

Job description

View original posting ↗

At PDI Technologies, we empower some of the world's leading convenience retail and petroleum brands with cutting-edge technology solutions that drive growth and operational efficiency.

By “Connecting Convenience” across the globe, we empower businesses to increase productivity, make more informed decisions, and engage faster with customers through loyalty programs, shopper insights, and unmatched real-time market intelligence via mobile applications, such as GasBuddy. We’re a global team committed to excellence, collaboration, and driving real impact. Explore our opportunities and become part of a company that values diversity, integrity, and growth.

Role Overview:

As a Data Engineer IV, you will serve as a senior technical contributor responsible for designing, developing, and optimizing scalable cloud-based data solutions that enable enterprise analytics, reporting, and business intelligence. You will lead the delivery of complex data integration initiatives, establish engineering best practices, and provide technical guidance to other engineers. This role requires a strong understanding of modern data engineering practices and a conceptual understanding of data architecture principles to design scalable, maintainable, and governed data solutions while partnering with business and technology teams to solve complex business problems.

Key Responsibilities

Design, develop, and optimize scalable cloud-based data pipelines that support enterprise analytics, reporting, and business intelligence.
Lead the development of complex data integration solutions using AWS-native technologies and modern data engineering practices.
Design scalable data models, ingestion frameworks, and transformation processes that support reliable, high-quality analytics.
Apply data architecture principles when designing scalable, secure, and maintainable data pipelines, data models, and integration solutions.
Establish and promote engineering standards, reusable frameworks, and best practices that improve platform reliability, scalability, and maintainability.
Partner with business stakeholders to translate reporting and analytics requirements into technical solutions.
Drive continuous improvement through automation, infrastructure as code, CI/CD, and DevOps best practices.
Lead troubleshooting and resolution of complex data platform, integration, and performance issues.
Mentor and provide technical guidance to other data engineers through code reviews, knowledge sharing, and best practice adoption.
Evaluate emerging technologies and recommend improvements that enhance platform performance, scalability, security, and operational efficiency.
Support data governance initiatives by promoting data quality, metadata management, and engineering standards across the data platform.

Qualifications

Bachelor's degree in computer science, Information Technology, Engineering, or a related field, or equivalent practical experience.
8+ years of experience in data engineering, cloud data platforms, or related software engineering roles.
Expert experience developing cloud-based data solutions using AWS technologies such as S3, Glue, Redshift, AppFlow, Lake Formation, Step Functions, and related services.
Advanced proficiency with SQL, Python, and PySpark for developing scalable ETL/ELT solutions.
Practical experience with applying AI/ML techniques to data engineering problems, such as automated data quality checks, anomaly detection, or intelligent pipeline monitoring.
Practical experience developing semantic and contextual layers within a data lake house.
Strong understanding of dimensional modeling, data warehousing, data lakehouse concepts, Apache Iceberg, Parquet, and modern data engineering practices.
Experience integrating enterprise platforms such as Salesforce, NetSuite, and other SaaS applications.
Strong understanding of modern data engineering practices with conceptual knowledge of data architecture principles, including data modeling, governance, metadata management, and scalable cloud data platforms.
Experience with Infrastructure as Code (Terraform), Git, Azure DevOps, and CI/CD pipelines.
Demonstrated ability to mentor engineers, influence technical decisions, and drive engineering best practices without formal people leadership.
Strong analytical, problem-solving, and communication skills with the ability to collaborate across technical and business teams.

Behavioral Competencies

Ensures Accountability

Manages Complexity

Communicates Effectively

Balances Stakeholders

Collaborates Effectively

PDI is committed to offering a well-rounded benefits program, designed to support and care for you, and your family throughout your life and career. This includes a competitive salary, market-competitive benefits, and a quarterly perks program. We encourage a good work-life balance with ample time off [time away] and, where appropriate, hybrid working arrangements. Employees have access to continuous learning, professional certifications, and leadership development opportunities. Our global culture fosters diversity, inclusion, and values authenticity, trust, curiosity, and diversity of thought, ensuring a supportive environment for all.

Employment type

Full-time

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay: No pay amount identified in the saved description.
Location & working pattern: Chennai
- Collaborates Effectively PDI is committed to offering a well-rounded benefits program, designed to support and care for you, and your family throughout your life and career. This includes a competitive salary, market-competitive benefits, and a quarterly perks program. We encourage a good work-life balance with ample time off [time away] and, where appropriate, hybrid working arrangements. Employees have access to continuous learning, professional certifications, and leadership development opportunities. Our global culture fosters diversity, inclusion, and values authenticity, trust, curiosity, and diversity of thought, ensuring a supportive environment for all. Employment type
Work authorization: No clear work-authorization passage found. Eligibility is unconfirmed.

Open source at jobs.lever.co ↗Read the full description ↓

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Upload resume Add LinkedIn