Top Data & Analytics Jobs

Designs and maintains scalable ETL pipelines, data models, integrations, cloud databases, and healthcare data infrastructure. Ensures security, HIPAA/HITRUST compliance, reliability, monitoring, and documentation while collaborating with product, engineering, and clinical teams. Requires strong SQL and Python expertise, modern data warehousing and orchestration experience, cloud platform knowledge, and familiarity with healthcare interoperability and claims data.

Own and define the technical direction of Dubsado’s data infrastructure as its first dedicated data hire. Assess and improve existing pipelines, warehouse systems, analytical models, reliability, quality, and observability. Build scalable data infrastructure, establish engineering standards and guardrails, support AI and customer-facing data features, and collaborate with engineering, product, and business stakeholders. Over time, expand contributions to backend services, infrastructure, and agentic systems while distributing data ownership across engineering.

Lead Data Engineer responsible for designing, maintaining, and improving data pipelines and platform infrastructure across ingestion, streaming, transformation, and delivery. The role uses Airflow, Spark, Iceberg, Kafka, Flink, dbt, Terraform, and GCP. Responsibilities also include defining data contracts, documenting systems, optimizing performance, reviewing code, supporting access controls and compliance, and collaborating with stakeholders and teammates.

Design and operate a large-scale AI/ML data platform spanning ingestion, lakehouse storage, cataloging, governance, vector search, dataset versioning, feature and embedding pipelines, observability, and low-latency retrieval. The role owns production reliability and performance, establishes data standards, supports reproducible model training, manages petabyte-scale storage, and mentors engineers while leading technical architecture.

Designs, builds, and maintains real-time data ingestion pipelines supporting Navy, DoD, and Intelligence Community missions. Responsibilities include monitoring data quality and feed health, implementing resilient streaming pipelines, automating alerts, conducting incident response and root cause analysis, visualizing operational trends, and collaborating with engineering, security, and governance teams. The role requires Python and Bash scripting, production data pipeline experience, and on-site work in Camp Smith, Hawaii.

Build and own production data pipelines, warehouse models, metric definitions, testing, monitoring, reconciliation, and alerting. Partner with Finance and other teams to create reliable datasets for usage, revenue, costs, margins, reporting, self-service analysis, and AI-assisted querying. Improve source data quality, investigate discrepancies, and establish a maintainable data foundation.

Designs, builds, and owns enterprise data infrastructure supporting analytics, machine learning, and AI applications. Responsibilities include developing scalable ETL/ELT pipelines, API and database integrations, data models, ingestion frameworks, lake and warehouse architectures, Power BI reporting assets, data quality monitoring, governance, lineage, and reproducibility practices. The role partners with data scientists, machine learning engineers, business teams, and IT while supporting healthcare data environments and third-party data negotiations.

Build and maintain production batch and streaming data pipelines, reusable ingestion and transformation components, and shared engineering patterns. Collaborate with platform and domain teams to translate requirements into secure, performant, testable, and observable pipelines. Integrate data quality, governance, monitoring, orchestration, incident response, and CI/CD practices while supporting documentation and enablement for common data engineering capabilities.

Maintain and administer Microsoft SQL Server databases supporting healthcare research administration, compliance, reporting, and operations. Design schemas and tables; develop and optimize stored procedures, queries, scripts, utilities, and reports; manage scheduled jobs; monitor performance, security, backups, recovery, and data integrity; troubleshoot database and application issues; coordinate with web developers; document solutions; and provide technical recommendations to research leaders.

Build Hyperbolic Labs’ data infrastructure from the ground up, owning the data warehouse, ingestion pipelines, data modeling, reliability, governance, monitoring, troubleshooting, and performance tuning. Partner with engineering and analytics teams to support growing products, data sources, BI, and reporting. The role requires deep PostgreSQL expertise, large-scale data experience, and independent ownership of production data systems.

Leads data engineering teams in designing, developing, and supporting scalable batch and streaming data solutions. Responsibilities include data pipeline development, architecture, governance, security, platform optimization, production support, technical mentorship, stakeholder collaboration, and delivery leadership. The role requires hands-on engineering with Python or similar languages, modern data technologies, cloud platforms, DevOps practices, and people-management responsibilities.

Build and operate production data pipelines and warehouse models for a global energy trading platform. Develop Python pipelines orchestrated with Prefect, create tested Snowflake models with dbt, migrate legacy Oracle systems, integrate diverse data technologies, and implement quality, freshness, monitoring, and alerting controls. The role also supports AI-ready data, AWS services, platform documentation, and direct collaboration with analysts and desk users.

Designs, implements, and sustains secure mission data pipelines for the Department of the Air Force’s DIFC2 program. Responsibilities include mission data architecture, interface and schema definition, ETL and transformation development, API integration, monitoring, documentation, and RMF compliance. The role requires collaboration with government, cybersecurity, and mission partners to deliver reliable, interoperable data flows in a defense environment.

Build and optimize data pipelines, backend services, forecasting systems, dashboards, and automated workflows supporting Starlink ground-network inventory, logistics, deployment, and reliability. Integrate ERP/MRP and logistics systems, manage hardware demand forecasting, improve supply-chain processes, monitor operational metrics, and support emergency deployments. The role requires collaboration across engineering, infrastructure, logistics, and program teams, with up to 25% travel and occasional extended or weekend hours.

Lead the modernization of a healthcare data platform from an MSSQL XML object store to a scalable AWS architecture. Evaluate AWS storage and query services, design SQL reporting layers, architect data migration and metadata strategies, optimize performance and cost, and build CI/CD and infrastructure-as-code pipelines. Partner with business stakeholders, analysts, and C#/.NET engineers to deliver accessible data models and reliable integrations. Document architecture, data flows, and migration processes while supporting healthcare data and compliance requirements.

Supports the design and development of scalable end-to-end data pipelines and cloud data platforms. Responsibilities include improving data reliability and quality, implementing data management practices, supporting automation and process improvements, ensuring secure and cost-effective solutions, and recommending system enhancements. The intern collaborates with global teams and gains hands-on experience in data engineering, project coordination, and innovation management.

The Principal Data Engineer designs and builds scalable cloud-native data platforms, pipelines, frameworks, and governed data products supporting analytics, reporting, AI, and operational workloads. Responsibilities include Databricks, Spark, Delta Lake, Azure, SQL Server, batch and streaming processing, data integration, performance optimization, governance, modernization, troubleshooting, architecture reviews, and mentorship. The role provides senior technical leadership without direct people management and supports insurance-domain data across policy, claims, billing, finance, and regulatory functions.

Supports implementation and stabilization of inbound and outbound healthcare data processes. Ingests, transforms, validates, and reconciles Medicaid claims and eligibility feeds from Gainwell, Arcadia, DHCS, and other sources. Establishes data-quality, refresh, completeness, and reconciliation controls for PRISM, case creation, and reporting. Supports Atrezzo interfaces, data exchanges, production analytics, troubleshooting, root-cause analysis, stakeholder communication, and implementation workstreams.

Designs and maintains scalable data architectures, ETL workflows, batch and real-time pipelines, and SQL/NoSQL storage solutions supporting intelligence operations. Ensures data quality, governance, security, compliance, and performance across structured and unstructured intelligence datasets. Documents schemas and data lineage, collaborates with analysts and data scientists, and participates in technical and mission-planning forums.

Designs and maintains scalable data architectures, ETL workflows, batch and real-time pipelines, and SQL/NoSQL storage for intelligence operations. Ensures data quality, governance, security, compliance, documentation, and lineage across multi-INT datasets. Collaborates with analysts and technical teams to translate intelligence requirements into secure solutions and participates in mission planning and coordination forums.

Designs and maintains scalable data architectures, ETL workflows, batch and real-time pipelines, and SQL/NoSQL storage solutions supporting intelligence operations. Ensures data quality, governance, security, lineage, and compliance with IC and DoD standards. Collaborates with analysts and technical teams to deliver reliable intelligence data and participates in mission-planning and coordination forums.

Supports AI and cloud solution development by extracting, transforming, standardizing, and integrating text, JSON, geospatial, and other datasets. Assists with automated data ingestion, data services, pipelines, and machine learning algorithm integration for testing and operational deployment. Coordinates data requirements with project managers, customers, vendors, software engineers, architects, and data teams while managing changing priorities in a national security environment.

Designs, develops, and optimizes scalable Azure-based data engineering solutions, including lakehouses, warehouses, ETL/ELT pipelines, Databricks notebooks, and analytics workflows. The role supports enterprise reporting, AI and machine learning initiatives, feature engineering, Generative AI, and MLOps. Responsibilities include performance tuning, CI/CD automation, production support, technical design, lifecycle management, stakeholder collaboration, and translating business requirements into secure, reliable data platforms.

Designs, develops, tests, maintains, and optimizes data pipelines and software systems using SQL, Python, and Apache Airflow. Supports technical projects, documents systems, troubleshoots application performance, evaluates user requirements, and develops technical specifications. Collaborates with epidemiologists, statisticians, and researchers, while mentoring staff and translating academic research needs into software solutions.

Build and operate production-grade AML data products, ETL pipelines, data models, integrations, and ML-ready datasets. Ensure data quality, lineage, security, governance, observability, reliability, and regulatory compliance. Support transaction monitoring, customer segmentation, risk rating, sanctions screening, and financial crime prevention initiatives. Lead architecture decisions, production support, incident response, CI/CD improvements, automated testing, code reviews, mentoring, and engineering standards.