Top Tech Jobs & Startup Jobs in NYC, NY

Year-long apprenticeship to train entry-level candidates in AI, data engineering, cloud, and software development through structured learning, hands-on projects, mentorship, and industry certifications. Apprentices work on data engineering, cloud modernization, generative AI/LLM projects, and internal automation while learning responsible AI, data governance, and consulting skills, then transition into full-time STS roles.

Build and productionize AI/ML solutions on a modern AWS federal data platform: implement RAG/vector stores, develop and validate models and pipelines, automate via Airflow/Glue/Spark, integrate with ETL metadata, ensure security/compliance, write tests and documentation, and support agile delivery.

Design, build, and operate large-scale AWS-based ETL pipelines using Glue/PySpark to ingest, transform, and curate multi-format data into Apache Iceberg tables. Ensure data quality, metadata management, semantic layer creation (Trino/Athena), CloudFormation deployments, documentation, and compliance within a FedRAMP federal agile environment.

Build and maintain AWS-based ETL pipelines (Glue/PySpark, MWAA/Airflow, Lambda) to ingest and process terabytes of financial data into an S3 data lake using Iceberg/Parquet. Implement metadata, monitoring, tests (90% coverage), materialized views (Trino/Athena), CloudFormation deployments, documentation, and support agile delivery and operations for federal clients.

Serve as a data quality and QA engineer on a federal data platform: build automated AWS Glue/Deequ data quality checks, validate schemas and ETL pipelines, create and run unit/integration tests with 90% coverage, support IV&V and UAT, perform static/security scans, produce test documentation, monitor production ETL, and collaborate with data stewards and IV&V teams.