Top Data & Analytics Jobs

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.

Lead strategy, roadmap, and adoption for an enterprise data domain by defining authoritative business definitions, delivering governed reusable data products, coordinating global delivery, ensuring data quality and governance, and measuring trust, reuse, adoption, and business value across analytics, reporting, operations, and AI use cases.

Processes and audits data in internal databases and Ultrapipe, ensuring accurate data entry and data integrity. Analyzes discrepancies and trends, prepares internal and client-facing reports, and drafts 2D isometric drawings using AutoCAD or related software. The role requires strong organization, attention to detail, problem-solving, communication, and the ability to meet deadlines while managing changing priorities.

Support execution and adoption of enterprise data governance standards by translating governance decisions into actionable plans, tracking work in JIRA, and delivering executive-ready metrics, dashboards, and scorecards. Perform fit-gap and readiness assessments, analyze complex datasets to surface risks and opportunities, and partner with domain, architecture, platform, and business teams to drive sustained governance adoption and measurable outcomes.

Designs and oversees scalable data platforms, warehouses, lakehouses, pipelines, ETL processes, dimensional models, and Spark workloads. Integrates AI/ML capabilities, data governance, lineage, testing, monitoring, and performance optimization. Collaborates with engineering, product, DevOps, and security teams to support tracking, analytics, and business insights. The role also mentors engineers and analysts and manages software delivery using AWS DevOps, CI/CD, and Terraform practices.