Top Data & Analytics Jobs

Build trusted, secure, and repeatable data pipelines, transformations, data products, retrieval layers, and semantic data assets. Assess data quality, lineage, governance, privacy, and access constraints; support AI retrieval, embeddings, vector stores, and grounding strategies. Create test and de-identified datasets, implement monitoring and quality checks, document data assets, and ensure reliable data for AI products, control-group testing, and production handoff.

Lead design and implementation of large-scale Azure cloud data systems and ETL/ELT pipelines using Databricks, Spark, Snowflake and LLM integrations. Build AI-driven solutions, optimize SQL performance, define architecture and best practices, mentor engineers, collaborate with stakeholders, and drive scalable, secure data platforms for analytics and machine learning.

Design, develop, test, document, and maintain scalable big data applications and cloud data platforms using Python, PySpark, Scala, Azure, Spark, Kafka, and Airflow. Build analytics rule engines, predictive algorithm frameworks, automation solutions, and AI-powered applications. Optimize performance, migrate applications, enforce code quality, support production systems, and collaborate across teams in an Agile environment.

Loads, analyzes, validates, and reports external healthcare data. Collaborates with developers, business teams, clients, and leadership to improve data quality, resolve issues, interpret requirements, identify trends, and communicate analytical findings and recommendations. Uses SQL, relational databases, reporting tools, spreadsheets, and AI assistants to support complex projects and payer-platform initiatives.

Designs, builds, and operates scalable enterprise data platforms and batch or streaming pipelines using Azure, Databricks, Snowflake, Delta Lake, and Azure Data Factory. Develops PL/SQL, Python, and Unix-based processing solutions, enables Generative AI workflows, and drives data architecture, governance, quality, security, and DevOps practices. Leads modernization and production support, partners with business and technical stakeholders, mentors engineers, and provides technical leadership for AI-enabled data solutions.

Leads enterprise data engineering and analytics initiatives using Databricks, Delta Lake, Spark, and PySpark. Designs dimensional, semantic, and context-layer models; builds scalable ETL/ELT pipelines; optimizes performance and cloud costs; and establishes data governance, quality, lineage, and monitoring standards. Partners with technical and business stakeholders, mentors engineers, conducts architecture reviews, and influences enterprise data platform strategy. Supports reporting, self-service analytics, AI/ML, and regulated healthcare data use cases.

Designs and maintains scalable ETL/ELT pipelines using Databricks, Snowflake, Python, Teradata, and Airflow. Builds data solutions for reporting, analytics, and AI/ML workloads; performs data quality validation, analysis, tuning, and operational monitoring. Collaborates with business and technical teams, supports deployments and issue resolution, applies CI/CD practices, and ensures data governance, security, and healthcare regulatory compliance.

Designs and optimizes Snowflake data pipelines for clinical and claims data supporting HEDIS processing, quality analytics, chart abstraction, and care gap identification. Integrates AI, machine learning, and NLP models into healthcare data workflows; implements data quality, governance, security, and HIPAA-compliant practices. Partners with clinical quality and reporting teams to translate HEDIS specifications into automated solutions, while mentoring engineers and advancing MLOps and DataOps practices.

Analyze Medicaid and T-MSIS data to support healthcare payment model implementation and operations. Translate policy requirements into SQL specifications, analytic code, payment calculations, attribution methodologies, and quality measures. Assess data quality across states and delivery systems, validate outputs, document methodologies, and prepare reports for technical and non-technical audiences while collaborating with policy, operations, and analytics teams.

Leads a team delivering real estate planning analytics, dashboards, reporting, and insights. Sets the analytics roadmap, modernizes technology through automation and AI, partners with executives and technical teams, and translates business needs into strategic recommendations. The role supports workplace portfolio decisions, occupancy strategy, and workforce location forecasting while requiring SQL, data warehouse, visualization, stakeholder management, and people leadership expertise.