Top Remote Data & Analytics Jobs

Builds and maintains scalable data pipelines and cloud infrastructure supporting an AI biomedical research platform. Responsibilities include ingesting, harmonizing, validating, and documenting multimodal neurodegeneration datasets; managing cloud storage, compute, permissions, and costs; implementing de-identification and data governance workflows; supporting research data repositories and AI/ML teams; and maintaining data lineage, catalogs, and technical documentation. The role requires strong Python and SQL skills, software engineering discipline, cloud experience, and neurodegeneration research data expertise.

Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.

Lead design and implementation of data architecture and reliable ETL processes to move data between heterogeneous sources and targets. Troubleshoot and resolve data architecture issues, collaborate with business analysts and technology teams, set up and test systems, and optimize ETL performance to support domestic resilience initiatives.

Build and maintain product analytics dashboards, validate and QA event tracking, translate event data into analytics-ready datasets, run funnels/cohorts/retention analyses, support A/B testing, and surface actionable product insights to Product, Growth, and Data stakeholders.

Lead and sustain enterprise master data operations (Material, Customer, Vendor, Pricing), enforce governance and SOX controls, drive data quality via KPIs and continuous improvement, support MDM/ERP initiatives, manage third-party providers, and develop data dictionaries, metrics, and process documentation.

Support PALU by building reproducible code and ETL pipelines to transform program data, develop dashboards and automated reports, design and deploy ODK/XLSForms and DHIS2 forms, monitor data quality, provide field technical assistance and training, and integrate MEL insights into program decision-making and proposals.

The Senior Data Engineer will design and develop scalable data architectures, manage ETL processes, optimize databases, and implement MLOps pipelines, promoting data-driven decision-making across the organization.

Responsible for building data models, developing ELT pipelines, implementing data quality checks, and utilizing best practices in data engineering and healthcare analytics.

Design, build, and maintain data pipelines, dashboards, and predictive models. Analyze large datasets to generate actionable insights, collaborate with stakeholders, ensure data quality and governance, and document/share analytics best practices to support Marketing, Product, Operations, and Workforce teams.

Build and maintain data infrastructure, integrate veterinary partner systems, develop dbt models and pipelines, provide analytics modeling, testing, reporting, and deliver actionable insights to customers and internal teams.