Top Data & Analytics Jobs

Develops and implements data engineering and integration solutions for intelligence-community applications. Maps and models data transformation routines, supports ingestion into corporate repositories, documents data flows, and works with schemas, structured data, databases, smart data systems, and entitlements. Requires extensive systems engineering experience and an active TS/SCI clearance with current polygraph.

Design, build, operate, and optimize large-scale data pipelines and foundational data platforms for healthcare datasets. The role focuses on Python, SQL, Spark, Airflow, AWS, storage optimization, schema evolution, data quality, observability, troubleshooting, CI/CD, and production support. The engineer will develop trusted data products, improve platform reliability and efficiency, contribute to architecture and technical direction, collaborate cross-functionally, and mentor teammates while using AI-assisted engineering tools.

Supports secure data operations within the SUNet environment, including ingestion, storage, transfers, validation, documentation, access management, troubleshooting, and data lifecycle activities. Maintains inventories and technical records, coordinates Change Requests and user onboarding, manages cloud and on-premises storage, and develops scripts for automation. The role supports Department of Defense AI and autonomy initiatives while collaborating with government, cybersecurity, engineering, vendor, and AI/ML stakeholders.

Develop and operate data pipelines supporting a federal analytics and business intelligence platform. Responsibilities include ingesting, processing, storing, and securely transferring data; deploying models; automating ingestion; maintaining applications; improving pipeline reliability; and implementing API-first, version-controlled, tested solutions in an Agile environment. The role collaborates with data scientists, architects, engineers, product managers, and federal stakeholders.

Build customer-facing data products for the single-family rental market. Responsibilities include architecting real estate data models, designing reliable data pipelines and workflows, shaping data platform architecture, establishing engineering standards, and developing real estate domain expertise. The role partners with data science and product teams and requires leadership in scalable data engineering.

Designs and implements secure, scalable data infrastructure for intelligence weapons systems. Responsibilities include translating requirements into data models and pipelines, integrating multiple data sources, monitoring and optimizing workflows, documenting data processes, and supporting data architecture. The role requires advanced SQL, Python, data modeling, pipeline operations, and collaboration with government customers and cross-functional teams.

Designs and implements scalable data pipelines, cloud data platforms, storage solutions, and analytics infrastructure. The role focuses on Snowflake and AWS architecture, migrating legacy systems to cloud environments, developing Python and SQL data-processing logic, orchestrating workflows, and implementing Infrastructure-as-Code and CI/CD. The engineer also contributes to data governance, quality, observability, stakeholder communication, mentoring, and technical leadership.

Designs, develops, and optimizes scalable batch and near-real-time data pipelines and platforms using Snowflake, AWS, Python, DataStage, and Control-M. Builds data models, ensures data quality and governance, tunes performance and costs, supports production operations, and enables analytics and AI/ML use cases. Collaborates with engineering, data science, BI, platform, and business teams in Agile environments.

Designs, builds, and supports scalable data pipelines, integrations, transformations, and services for Mayo Clinic’s biomedical research platform. Works with genomic, omics, clinical, laboratory, imaging, and multimodal datasets; harmonizes data, maintains metadata and provenance, validates quality, and enables governed access. Partners with investigators, bioinformaticians, scientists, and analytics teams to support research, machine learning, and precision medicine applications using Google Cloud and modern data engineering tools.

Design, deploy, and maintain global data platform infrastructure with emphasis on multi-region Databricks orchestration. Lead system architecture, optimize Databricks (Delta, Spark, Unity Catalog), implement IaC with Terraform, build CI/CD pipelines, troubleshoot platform issues, and collaborate with cross-functional teams to meet technical, governance, and performance requirements.

Develop and maintain data pipelines, scalable data models, analytics datasets, and Power BI reporting solutions for renewable energy construction and preconstruction operations. Integrate cost, labor, project, scheduling, and operational data to support benchmarking, forecasting, estimate accuracy, and predictive analytics. Collaborate with estimators, engineers, procurement, project controls, operations, and leadership while using Databricks, Python, SQL, GitHub, and AI-enabled development practices.

Develops data analytics solutions for intelligence mission applications, including structured and unstructured data enrichment, conversion, ingestion, characterization, and analysis. Uses statistical methods, machine learning, metadata processing, schemas, databases, and big data frameworks to identify patterns and deliver visualized datasets. Collaborates with mission customers, software engineering teams, data stewards, and stakeholders. Requires active TS/SCI with current polygraph, eight years of software development experience, and an approved technical certification.

Develop and implement data engineering solutions for web applications supporting intelligence community data custodians. Identify, map, and model transformations for ingesting diverse datasets into corporate repositories, document data flows, and support compliant data routing. The role involves integrating vendor products, developing scalable clustered or cloud storage, defining system requirements, and leading agile engineering efforts. Candidates must have extensive systems engineering experience and an active TS/SCI clearance with current polygraph.

Develop data analytics and visual analytic applications using structured and semi-structured data. Design enterprise databases, build relational database systems, integrate data systems, and optimize data pipelines and performance. The role uses Java, AWS, Spark, Scala, SQL, PostgreSQL, NiFi, Informatica, Linux, and ETL technologies to support actionable intelligence applications. An active Top Secret/SCI-eligible clearance is required, with potential CI polygraph eligibility.

Build and operate production pipelines for legal records from PACER, court systems, opinions, PDFs, scans, XML, and HTML. Develop LLM-assisted extraction workflows, validate data quality, optimize SQL, and support RAG and semantic search products. Manage AWS S3 and RDS systems within security guardrails while collaborating with engineering teams. The role requires strong Python and SQL skills, legal data experience, document extraction expertise, and autonomous problem-solving with large, messy datasets.

Own MISUMI’s Snowflake data platform, dbt project, and ELT pipelines. Administer security, access, performance, and cost controls; build trusted dimensional models; resolve pipeline and data-quality issues; manage GitHub workflows; translate business needs into data solutions; and promote disciplined AI-assisted engineering practices. Mentor analysts and engineers, lead technical reviews, maintain documentation and QMS processes, and support regulated data environments.

Lead enterprise data engineering efforts supporting defense missions. Responsibilities include prioritizing technical tasks, mentoring engineers, conducting code reviews, translating government requirements into scalable data architectures, developing Databricks ETL/ELT pipelines with Python, PySpark, and SQL, troubleshooting pipeline performance and reliability, and documenting systems. The role collaborates with government stakeholders, product owners, data scientists, analysts, and technical teams to deliver secure, high-throughput data platforms and actionable insights.

Designs and automates data validation, profiling, testing, monitoring, and quality frameworks for multi-source cloud data. The role uses Azure Synapse, Databricks, SQL, Python, Scala, Collibra, and Profisee to detect anomalies, enforce governance, and improve data reliability. Responsibilities include developing automated test plans, analyzing structured and unstructured datasets, supporting Azure data engineering workflows, and collaborating with engineers, analysts, data scientists, and product teams. A Public Trust or Suitability/Fitness determination may be required.

Designs and maintains scalable Azure data pipelines and ETL/ELT solutions across data lakes, warehouses, lakehouses, streaming platforms, and enterprise sources. Builds integrations using Azure Data Factory, Synapse, Databricks, Spark, Kafka, and related services; applies security, governance, monitoring, and performance optimization practices. Develops Power BI dashboards, reports, data models, and visualizations, while supporting analytics and AI/ML use cases. Collaborates in Agile teams and automates deployments through DevOps and CI/CD practices.

Designs and develops AWS data pipelines and automated document-processing workflows for structured and unstructured data. Builds chunking, embedding, vector indexing, semantic search, knowledge bases, and RAG integrations. Develops AI agents using Amazon Bedrock and Claude technologies, deploys them through AgentCore, and maintains GitHub Actions CI/CD pipelines. Optimizes systems for scalability, reliability, security, and performance. Requires remote work in western U.S. time zones and travel to client workshops or meetings.

Designs and operates data infrastructure for a clinical trial platform. Builds pipelines that extract, normalize, validate, and link information from clinical documents and publications into Aurora and GraphDB. Develops embeddings, vector search, RAG workflows, data-serving APIs, lineage tracking, and regulatory audit trails. The role also requires AWS-based orchestration, clinical data quality controls, biomedical knowledge graph modeling, and deployment automation using infrastructure-as-code and containerization.

Build and lead Greenlight Rent’s data foundations, including event models, ingestion, warehouses, transformations, APIs, services, and data products. Ensure data reliability, security, compliance, and correctness for financial reporting and business operations. Partner with product, finance, and operations to deliver measurable outcomes, make technical tradeoffs, establish engineering and data-quality standards, mentor engineers, and lead high-impact projects while remaining hands-on in production software development.

Leads data engineering initiatives embedded with infrastructure teams. Designs governed data products, integrations, data contracts, quality controls, metadata, lineage, and standardized data models. Reconciles infrastructure asset inventories, resolves data discrepancies, and partners with engineering, product, and governance stakeholders to improve data completeness, accuracy, interoperability, security controls, and enterprise analytics.

Build and operate scalable data pipelines and platforms that transform LiDAR, imagery, and GPS sensor data into reliable geospatial deliverables. Responsibilities include automating ingestion, AI processing, quality checks, monitoring, workflows, and data access; partnering with Data Operations and GIS teams; and improving AWS processing performance and cost. The role requires end-to-end ownership, including system design, operation, and on-call support.

Builds and maintains cloud-based data pipelines, transformations, semantic views, conformed dimensions, and analytical data models supporting reporting and AI/ML. Implements data quality checks, documentation, lineage, testing, release-readiness evidence, and defect resolution. Collaborates with data owners, governance, engineering, security, product, and customer teams to deliver reliable, governed data products. The role supports enterprise data modernization, migrations, DataOps, and production data platforms for a federal client.