Responsibilities:
Design, develop, and maintain scalable ETL pipelines to process and transform large-scale datasets.
Integrate structured and unstructured data from multiple sources, ensuring quality, security, and consistency.
Collaborate with data scientists, analysts, and software engineers to deliver well-structured and accessible datasets.
Build and optimize data infrastructure using big data technologies such as Apache Spark, Hadoop, and Kafka.
Deploy and manage cloud-based data solutions on AWS, GCP, or Azure.
Monitor and troubleshoot data pipeline performance, ensuring reliability and efficiency.
Implement data governance, security, and compliance best practices.
Drive automation, testing strategies, and continuous improvements in data engineering workflows.

Qualifications:
5 years of related experience with a Bachelor’s degree or equivalent work experience.




Advanced proficiency in SQL and experience with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, etc.).
Robust programming skills in Python, Java, or Scala for data processing and automation.
Deep expertise in ETL processes, data modeling, and data warehousing.
Hands-on experience with big data frameworks such as Apache Spark, Hadoop, or Kafka.
Proficiency in cloud platforms (AWS Redshift, Google BigQuery, Azure Synapse) and data infrastructure automation.
Experience optimizing data pipeline performance and scalability.
Strong problem-solving skills with the ability to work on complex, large-scale datasets.
Knowledge of data governance, security, and compliance best practices.
Excellent leadership, collaboration, and communication skills to work effectively across teams.

📌 Data Engineer (Chennai)
🏢 Numentica
📍 Chennai