Top Remote Data & Analytics Jobs

Collects and delivers market measurement data for in-store retail programs, supports test design and measurement planning, presents findings, and communicates insights to Sales and cross-functional stakeholders. The role manages multiple analyses and reports, ensures accuracy and timely delivery, and applies data interpretation, problem-solving, and stakeholder communication skills. Experience with analytics, consumer-packaged goods, media, agency environments, or Circana/NielsenIQ data is advantageous.

Designs, builds, and maintains enterprise lakehouse data pipelines, transformation layers, and data models. Develops scalable batch and streaming solutions using Spark, Kafka, and Flink; implements medallion architecture, data quality monitoring, and infrastructure as code. Troubleshoots performance and data incidents, participates in code reviews, collaborates on data modeling, and mentors junior and mid-level engineers.

Lead a Salesforce data engineering team to design, deliver, and support Salesforce-to-Salesforce integrations and migrations, data modeling, ETL/transformations, automation, and observability. Manage hiring, performance, and career development; partner with stakeholders; adopt AI/LLM agent tooling to automate workflows and improve data quality; reduce technical debt and document systems and processes.

Leads data and analytics engineering for Zero Trust maturity assessment and implementation measurement. Designs common data models, integrates and validates enterprise data, develops maturity and risk metrics, supports prioritization and gap analysis, and establishes data quality, lineage, traceability, and documentation practices. Partners with dashboard and automation specialists to streamline reporting and data refresh workflows.

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.