Degree in Computer Science, Software Engineering, Data Science, or equivalent
2+ years in data engineering, analytics, or AI/ML
Proficient in Python (ETL) and Spark (PySpark) for large-scale pipelines
Strong in SQL/Big Data frameworks (Spark SQL, Redshift, PostgreSQL)
Experience with Airflow (or similar), CI/CD (GitLab/Jenkins), and cloud platforms (AWS S3/EMR/Glue, Redshift, Docker, Kubernetes)
Knowledge of relational (PostgreSQL/Redshift) and NoSQL (MongoDB) databases
Skilled in data modeling, query optimization, and scalable storage solutions
Infrastructure as Code (Terraform/CloudFormation)
Familiarity with MLOps/LLMOps workflows
Strong problem-solving and cross-functional collaboration skills
Nice to Have
Exposure to serverless (AWS Lambda), vector DBs, data mesh/lakehouse
Experience with BI tools (Tableau, QuickSight, Grafana) and data quality frameworks (Deequ)
Involvement in GenAI/LLM POCs (RAG, Agentic AI, NL?SQL)
Client-facing/stakeholder management experience
Job Types: Full-time, Permanent
Benefits:
* Health insurance
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