Data Engineer

Requirements

• Degree in Computer Science, Software Engineering, Data Science, or equivalent experience
• 2+ years in data engineering, analytics, or related AI/ML role
• Proficient in Python for ETL/data engineering and Spark (PySpark) for large-scale pipelines
• Experience with Big Data frameworks and SQL engines (Spark SQL, Redshift, PostgreSQL) for data marts and analytics
• Hands-on with Airflow (or equivalent) to orchestrate ETL workflows and GitLab CI/CD or Jenkins for pipeline automation
• Familiar with relational (PostgreSQL, Redshift) and NoSQL (MongoDB) stores: data modeling, indexing, partitioning, and schema evolution
• Proven ability to implement scalable storage solutions: tables, indexes, partitions, materialized views, columnar encodings
• Skilled in query optimization: execution plans, sort/distribution keys, vacuum maintenance, and cost-optimization strategies (cluster resizing, Spectrum)
• Experience with cloud platforms (AWS): S3/EMR/Glue, Redshift and containerization (Docker, Kubernetes)
• Infrastructure as Code using Terraform or CloudFormation for provisioning and drift detection
• Knowledge of MLOps/LLMOps: auto-scaling ML systems, model registry management, and CI/CD for model deployment
• Strong problem-solving, attention to detail, and the ability to collaborate with cross-functional teams