AI Data Engineer

AI Data Engineer

About the Role

We are looking for an AI Data Engineer

What You’ll Do

• Design, build, and maintain end-to-end data pipelines for AI/ML workloads
• Develop high-quality, model-ready datasets by transforming, cleaning, and enriching raw data
• Build and manage feature stores and support ML engineers with feature engineering
• Collaborate with data scientists to understand model requirements and deliver optimized datasets
• Implement ETL/ELT workflows for real-time and batch data processing
• Optimize data systems for speed, scale, and cost efficiency
• Ensure data quality, governance, and documentation across pipelines
• Work with cloud-native tools for storage, orchestration, and automation

What We’re Looking For

• 2–5 years of experience as a Data Engineer or AI-focused Data Engineer
• Strong expertise in Python and SQL
• Experience with distributed processing tools: Apache Spark, Databricks, PySpark
• Hands-on experience with ETL/ELT orchestration (Airflow, dbt, Prefect, etc.)
• Good understanding of ML pipelines, feature stores, and AI workflows
• Familiarity with cloud platforms (AWS / Azure / GCP) and modern data architectures
• Experience working with APIs, data ingestion frameworks, and real-time streaming (Kafka is a plus)
• Strong problem-solving mindset and ability to work in fast-paced environments

Good to Have

• Experience with MLOps tools such as MLflow, Vertex AI, or Azure ML
• Knowledge of vector databases and feature engineering tools
• Exposure to LLM/GenAI data pipelines

Why Join Us

• Work on cutting-edge AI and analytics products
• Opportunity to influence architecture and build scalable systems from scratch
• Collaborative, growth-focused environment
• Real impact on product performance and customer experience