Data Engineer

As an AI-Driven Data Engineer at our organization, you will play a crucial role in building scalable data pipelines, optimizing data infrastructure, and enabling AI-powered analytics. Your responsibilities will include working with large datasets, modern data platforms, and AI-enabled tools to support data science, machine learning, and business intelligence initiatives. Key Responsibilities: - Strong proficiency in Python for data processing, ETL, and AI-enabled data workflows - Advanced SQL skills, including query optimization, indexing, joins, and analytical functions - Hands-on experience with ClickHouse, MongoDB, Redis, and ElasticSearch - Proficiency in Apache Spark/PySpark and working with data lakes and AI/ML data pipelines - Experience with ETL and data ingestion tools such as Apache NiFi - Familiarity with messaging and streaming platforms like Kafka, RabbitMQ, and ActiveMQ for real-time data processing - Experience with workflow orchestration frameworks such as Apache Airflow - Exposure to cloud platforms (AWS, GCP, or Azure) and their data services (S3, Redshift, BigQuery, Dataproc) supporting AI/ML workloads - Understanding of data warehousing, data modeling, and performance optimization techniques Qualifications Required: - Strong expertise in Python, SQL, distributed data systems, and modern data engineering frameworks - Exposure to AI-driven data workflows and intelligent automation In addition to the technical skills, we are looking for individuals who are willing to explore AI-driven technologies, continuously upskill, pay strong attention to detail, possess excellent problem-solving abilities, have strong communication skills to explain data concepts to stakeholders, and demonstrate strategic thinking with a focus on optimizing data workflows. As an AI-Driven Data Engineer at our organization, you will play a crucial role in building scalable data pipelines, optimizing data infrastructure, and enabling AI-powered analytics. Your responsibilities will include working with large datasets, modern data platforms, and AI-enabled tools to support data science, machine learning, and business intelligence initiatives. Key Responsibilities: - Strong proficiency in Python for data processing, ETL, and AI-enabled data workflows - Advanced SQL skills, including query optimization, indexing, joins, and analytical functions - Hands-on experience with ClickHouse, MongoDB, Redis, and ElasticSearch - Proficiency in Apache Spark/PySpark and working with data lakes and AI/ML data pipelines - Experience with ETL and data ingestion tools such as Apache NiFi - Familiarity with messaging and streaming platforms like Kafka, RabbitMQ, and ActiveMQ for real-time data processing - Experience with workflow orchestration frameworks such as Apache Airflow - Exposure to cloud platforms (AWS, GCP, or Azure) and their data services (S3, Redshift, BigQuery, Dataproc) supporting AI/ML workloads - Understanding of data warehousing, data modeling, and performance optimization techniques Qualifications Required: - Strong expertise in Python, SQL, distributed data systems, and modern data engineering frameworks - Exposure to AI-driven data workflows and intelligent automation In addition to the technical skills, we are looking for individuals who are willing to explore AI-driven technologies, continuously upskill, pay strong attention to detail, possess excellent problem-solving abilities, have strong communication skills to explain data concepts to stakeholders, and demonstrate strategic thinking with a focus on optimizing data workflows.