Data Engineer

About LetitbexAI

LetitbexAI is a fast-growing AI-driven technology company focused on building intelligent, scalable, and enterprise-grade solutions. We work at the intersection of AI, data engineering, cloud, and business transformation, helping organizations unlock real value from artificial intelligence.

Position: Data Engineer

Experience: 3-5 Years

Notice Period: Can be considered up 15 Days

Role Summary

Design and build scalable data pipelines, infrastructure, and systems to support ML model development and production deployment. Ensure data quality, governance, and efficient data flow across the organization.

Key Responsibilities

• Design and build scalable data pipelines for ML model training and inference
• Develop ETL/ELT processes for recruitment data from multiple sources
• Implement data quality checks, validation frameworks, and monitoring
• Build and maintain feature stores and feature engineering pipelines
• Design databases and data warehouse schemas optimized for ML and analytics
• Implement data governance, security, and compliance measures
• Optimize data storage and query performance for large scale datasets
• Build data APIs and infrastructure for real-time feature serving
• Document data lineage, dictionaries, and governance policies
• Collaborate with ML engineers to understand data requirements and optimize

Required Skills \& Experience

• 3-5 years of data engineering experience in production environments
• Strong proficiency in SQL and query optimization
• Experience with data pipeline orchestration tools (Airflow, Prefect, dbt, etc.)
• Knowledge of big data technologies (Spark, Hadoop) or cloud data solutions (Snowflake, BigQuery)
• Proficiency in Python or Scala for data processing
• Understanding of data warehouse design and dimensional modeling
• Knowledge of databases (both relational and NoSQL)
• Experience with version control and CI/CD practices
• Strong problem-solving and communication skills

Nice to Have

• Experience with ML infrastructure and feature stores (Tecton, Feast, etc.)
• Knowledge of cloud platforms (AWS, GCP, Azure)
• Experience with real-time streaming data (Kafka, Kinesis)
• Understanding of data governance and compliance (GDPR, CCPA)
• HR Tech or Vendor Management System domain knowledge