Data Engineer

As a Data Engineer, you will transform complex datasets into meaningful insights to drive data-driven decisions across HR, Finance, and Operations. You’ll work closely with AI Engineers, Data Scientist, and stakeholders to develop models, dashboards, and predictive analytics systems.

Core Responsibilities:

• Design and maintain scalable ETL pipelines to process structured and unstructured data from multiple sources.
• Build and optimize data warehouses, data lakes, and data marts to support downstream analytics and AI systems.
• Collaborate closely with data scientists and AI engineers to ensure clean, accessible, and reliable data.
• Implement data quality checks, monitoring, and logging to ensure data integrity and lineage.
• Automate data workflows using tools like Airflow, dbt, or custom Python scripts.
• Work with both structured (MySQL, PostgreSQL) and non-structured (pdf, images, ppt and many more) data sources.
• Ensure secure, efficient, and governed access to enterprise-grade datasets and APIs.
• Continuously improve data infrastructure based on usage feedback, scalability needs, and business goals.

Requirements Must-Have Skills

• Proficient in SQL and one programming language (Python, Scala, or Java)
• Solid understanding of data modeling, ETL design, and batch/streaming data processing
• Hands-on experience with modern data pipeline tools (e.g., Apache Airflow, dbt, or similar)
• Familiar with both relational (PostgreSQL, MySQL) and non-relational (MongoDB, S3, etc.) databases
• Experience working with large datasets and optimizing performance for data queries and storage
• Comfortable collaborating with data scientists, analysts, and backend engineers

Skills: Extract, Transform, Load (ETL), Data Infrastructure, Bash, Python, PostgreSQL, Linux, SQL