Description

You will design and implement scalable data architectures to support AI-driven solutions and business intelligence.

This role is on-site.

Responsibilities

• Architect and optimize data pipelines for structured and unstructured data.
• Design scalable ETL workflows to fuel AI/ML models.
• Engineer cloud-native data infrastructure on AWS, GCP, or Azure.
• Build and maintain data lakes, warehouses, and real-time streaming solutions.
• Automate workflows using orchestration tools like Airflow, Luigi, or Prefect.

Required Skills

• 5+ years of hands-on experience in data engineering.
• Strong expertise in Python and SQL.
• Proficiency with distributed frameworks including Spark, Hadoop, and Kafka.
• Deep understanding of data modeling, schema design, and warehousing using Snowflake, Redshift, or BigQuery.
• Experience with relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Cassandra.
• Knowledge of real-time and batch processing using Kafka, Flink, or Spark Streaming.
• Experience with automation, CI/CD, and infrastructure-as-code using Terraform, Docker, or Kubernetes.

Preferred Skills

• Ability to troubleshoot and optimize complex data workflows.

Any Graduate degree.

Key Skills

Education

Any Graduate