Top Data & Analytics Jobs

Reviews AI-generated documents, spreadsheets, and slide decks for accuracy, rigor, presentation quality, and domain-specific compliance. Evaluates outputs using quality rubrics, identifies factual and aesthetic errors, and provides structured written feedback. The role requires deep expertise in data quality and CRM operations, strong English fluency, and proficiency with Microsoft Office and Google Workspace. It is a fully remote, flexible independent-contractor engagement.

Analyzes operational, quality, productivity, recovery, and financial data to identify trends, risks, root causes, and improvement opportunities. Supports strategic initiatives through project planning, milestone tracking, reporting, and documentation. Contributes to Lean Six Sigma efforts, process mapping, governance, standardization, workflow analysis, and automation initiatives while translating findings into actionable business recommendations.

Analyzes customer data to identify trends, churn risks, and high-value audience segments. Builds Excel and SQL analyses, supports CRM audience requests through Jira, develops reporting, investigates performance changes, and presents actionable recommendations to cross-functional teams to improve customer retention and revenue.

Lead the design, development, scaling, and operation of enterprise data platforms, services, and pipelines. Own mission-critical systems, deliver complex multi-team projects, build analytics solutions, and improve data delivery processes. Partner with architects, engineers, analysts, data scientists, and business stakeholders to create reliable, observable, secure, and governed platforms. Provide technical leadership, evaluate technologies, establish engineering best practices, mentor engineers, and guide technical decisions across teams.

Leads data engineering and AI platform delivery for enterprise operations. Designs scalable AWS and Databricks architectures, builds ELT pipelines with Airflow, develops data models, and establishes governance, security, quality, monitoring, and compliance controls. Partners with stakeholders to translate business needs into production solutions, guides platform evolution, and supports AI-powered automation, agentic architectures, and enterprise integrations. Provides technical leadership and subject-matter expertise across data, analytics, and AI initiatives.

Designs and engineers scalable Azure and Databricks Lakehouse data platforms, including ingestion frameworks, batch and streaming pipelines, governed Bronze-to-Gold data models, quality controls, semantic layers, CI/CD, Infrastructure as Code, and access policies. The role translates enterprise architecture into reusable engineering solutions, guides delivery teams, troubleshoots technical issues, and partners with business stakeholders and data stewards to define metrics, requirements, and governance standards.

Performs geospatial analysis, develops GIS programs and user-facing tools, maintains authoritative spatial databases, and supports address geocoding and district boundary assignments. The role involves importing and reconciling spatial data, producing maps and reports, validating datasets, documenting metadata, evaluating data quality, and consulting with business users. Work supports a statewide public-sector system modernization program focused on address-based record assignment.

Build and maintain reliable data pipelines and architecture for large-scale IoT solar tracker deployments. Develop ingestion, transformation, validation, and monitoring tools using Go, Python, and SQL. Debug pipeline code, document workflows, maintain data quality, and collaborate with internal teams to improve analytics products. The role also involves keeping the data stack current and supporting scalable data infrastructure.

Administer enterprise databases and data warehouses, focusing on performance tuning, security, recovery, data modeling, ETL, and data integrity. Design Star, Snowflake, and normalized schemas; maintain data dictionaries; support reporting tools; create test environments; and assist with database software configuration. Collaborate with technical teams and stakeholders, provide user support, and ensure accessibility compliance. The role is hybrid in Austin, Texas, with three required onsite days weekly.

Designs and leads scalable Azure and Databricks Lakehouse data engineering solutions. Builds governed batch and streaming pipelines, Bronze-to-Silver transformations, curated Gold-layer models, semantic-layer integrations, CI/CD automation, and Infrastructure as Code. Establishes data quality, metadata, security, and Unity Catalog standards while optimizing performance and cost. Guides delivery teams through architecture, onboarding, debugging, and design reviews, and partners with business stakeholders and data stewards to define requirements and validate metrics.