Top Data & Analytics Jobs

Design, develop, and maintain OBIEE (RPD, reports, security, tuning) and Informatica ETL components (PowerExchange, data quality, replication, metadata). Work with Oracle 10g/11g, SQL/PLSQL, and data warehouse/data mart implementations. Support BI Publisher, upgrades, and migrations.

Hands-on Informatica developer responsible for MDM implementation and data integration using Informatica PowerCenter and Data Quality. Work with Oracle and SQL/PLSQL on Linux/Unix environments. Requires 8-10 years IT experience, minimum 2 years MDM, strong communication, independence, and a BE or equivalent.

Own and scale the data platform powering ReadyOn's real-time labor OS. Design and operate batch and real-time pipelines, transformations, and data services (Python, PySpark, Airflow, Glue, Snowflake, Postgres). Build connectors, observability, data quality, and feature-store infrastructure while partnering with AI, backend, and product teams and providing technical leadership and mentorship.

Design, implement, and maintain dbt/Snowflake ELT transformations to convert raw clinical and multimodal health data into trusted, analysis-ready models; enforce data quality, lineage, testing, CI/CD, and documentation; collaborate with clinical and ML teams to harmonize ontologies and support de-identification and ETL across health systems.

Design, build, and maintain automation workflows and data pipelines across admissions, education, career services, and billing. Create BI dashboards, ensure data accuracy, manage lightweight databases (e.g., Supabase), and support cross-functional teams to improve operational efficiency and scalability.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Build and scale Allocate's AWS-based data lakehouse and pipelines (batch and real-time). Model financial entities and integrate internal/third-party sources. Enable ML/AI workflows, vector and knowledge-graph integrations, CI/CD and containerized deployments, and collaborate with engineering to deliver reliable, production-grade data and AI infrastructure.

Lead enablement and coordination across domain teams to establish enterprise cloud data standards, platform onboarding, and data warehouse integration. Drive adoption of data engineering frameworks, reusable components, governance, data quality, stakeholder alignment, and continuous improvement to scale platform delivery across multiple teams.

Lead analytics and BI efforts to drive operational performance: build and maintain dashboards and ETL pipelines, analyze KPIs and drilling performance, support performance-improvement initiatives, collaborate with data scientists and BI/devops, and manage daily operational reporting and optimization tools.