Big Data Engineer - Python

Qcentrio; Chennai District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Qcentrio is hiring an experienced Data Engineer to design and implement scalable data infrastructure, including robust ETL/ELT pipelines for terabytes of data. You will work with Azure-based workflows, Spark/Hadoop processing, and data lakehouse architectures to ensure high performance and data quality across the lifecycle.

The role demands 5+ years of practical data engineering experience, strong Python and SQL abilities, and collaboration with cross-functional teams in a fast-paced

Qualifications

• 5+ years of hands-on experience in building scalable data infrastructure and systems.
• Advanced proficiency in Python and strong SQL skills.
• Experience with distributed computing frameworks like Apache Spark and Hadoop.
• Cloud development experience with Azure, AWS, or GCP.
• Knowledge of data lake / data lakehouse architectures and ETL optimization.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for processing large data volumes.
• Model and structure data for performance, scalability, and usability.
• Work with cloud infrastructure (preferably Azure) to build and optimize data workflows.
• Leverage distributed computing frameworks like Apache Spark and Hadoop for large-scale processing.
• Build and manage data lake/lakehouse architectures following best practices.
• Optimize ETL performance and manage cost-efficient data operations.
• Collaborate with data science, analytics, and software engineering teams.
• Ensure data quality, integrity, and security across the data lifecycle.

Skills

Python

SQL

Apache Spark

Hadoop

Azure

ETL

Data lake

Tools

Apache Airflow

Azure Data Factory

CI/CD for data pipelines

Job description

We are seeking an experienced and driven Data Engineer with 5+ years of hands-on experience in building scalable data infrastructure and systems. You will play a key role in designing and developing robust, high-performance ETL pipelines and managing large-scale datasets to support critical business functions. This role requires deep technical expertise, strong problem-solving skills, and the ability to thrive in a fast-paced, evolving environment.

Key Responsibilities :

• Design, develop, and maintain scalable and reliable ETL/ELT pipelines for processing large volumes of data (terabytes and beyond).
• Model and structure data for performance, scalability, and usability.
• Work with cloud infrastructure (preferably Azure) to build and optimize data workflows.
• Leverage distributed computing frameworks like Apache Spark and Hadoop for large-scale data processing.
• Build and manage data lake/lakehouse architectures in alignment with best practices.
• Optimize ETL performance and manage cost-effective data operations.
• Collaborate closely with cross-functional teams including data science, analytics, and software engineering.
• Ensure data quality, integrity, and security across all stages of the data lifecycle.

Required Skills & Qualifications :

• 7 to 10 years of relevant experience in bigdata engineering.
• Advanced proficiency in Python.
• Strong skills in SQL for complex data manipulation and analysis.
• Hands-on experience with Apache Spark, Hadoop, or similar distributed systems.
• Proven track record of handling large-scale datasets (TBs) in production environments.
• Cloud development experience with Azure (preferred), AWS, or GCP.
• Solid understanding of data lake and data lakehouse architectures.
• Expertise in ETL performance tuning and cost optimization techniques.
• Knowledge of data structures, algorithms, and modern software engineering practices.

Soft Skills :

• Strong communication skills with the ability to explain complex technical concepts clearly and concisely.
• Self-starter who learns quickly and takes ownership.
• High attention to detail with a strong sense of data quality and reliability.
• Comfortable working in an agile, fast-changing environment with incomplete requirements.

Preferred Qualifications :

• Experience with tools like Apache Airflow, Azure Data Factory, or similar.
• Familiarity with CI/CD and DevOps in the context of data engineering.
• Knowledge of data governance, cataloging, and access control principles.

Skills :

Python,Sql,Aws,Azure, Hadoop