Data Engineer IV
pditechnologies · Chennai ·
- Work mode
- Hybrid
- Category
- Data engineering
- Experience
- 8+ years
- Company size
- 501-1000
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Designs and maintains cloud-based data pipelines in AWS to integrate enterprise systems like Salesforce and NetSuite, enabling analytics and business intelligence for a global convenience retail and petroleum tech company.
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.
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.
Ensures Accountability
Manages Complexity
Communicates Effectively
Balances Stakeholders
Collaborates Effectively
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