Job Description

Qualifications

Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or equivalent experience 4+ 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
Job Types: Full-time, Permanent

Benefits:

* Health insurance