Top Data & Analytics Jobs

Design, develop, test, maintain, and support secure, scalable data solutions using Snowflake and Databricks. Lead technical design, author specifications, review code, mentor engineers, ensure SDLC, audit/security compliance, and drive technical strategy while collaborating with architects and business partners. Participate in Agile ceremonies, be on-call as needed, and travel occasionally.

Design, build, and optimize scalable cloud-based data pipelines using PySpark and Databricks. Develop and maintain ETL/ELT workflows, model data for warehousing in AWS Redshift, and tune performance. Troubleshoot production issues and work with Python and SQL to process large-scale distributed data. Prior domain experience in e-commerce, airlines, transportation, or logistics is desirable.

Design, build, and maintain ETL/data pipelines and data models using Databricks and cloud platforms. Support BI (Power BI) reporting and ML workflows, apply SQL and analytical skills to enable data-driven insights.

The Data Engineer/ETL Engineer will support cloud-based and on-prem application development, focusing on data management and analytics for defense and intelligence.

Implement and maintain scalable ETL/ELT pipelines and data warehouse structures, ensure data quality and governance, support Power BI/Alteryx reporting, collaborate with stakeholders and Senior Data Engineers, perform database performance tuning and testing, and document data models and pipelines to support fundraising, financial, and operational reporting.

Build and maintain production-grade data processing systems and foundational infrastructure for enterprise AI. Collaborate with researchers and engineers, deliver end-to-end implementations, transform unstructured data into performant datasets, and use distributed processing frameworks and modern analytics tooling to inform products and strategy.

Build and scale optimized data pipelines and data engine architecture to run ML models, reduce annotation costs, integrate foundation models for labeling and QA, use software/hardware-in-the-loop testing, and collaborate with DoD customers to understand requirements and support field events.

Lead Data Engineer to design, develop, test, implement, and support cloud-based big data solutions. Collaborate across Agile teams on distributed, streaming, and full-stack systems using Java/Scala/Python, RDBMS and NoSQL, Redshift/Snowflake, and cloud platforms. Mentor engineers, perform code reviews, and ensure performant, well-tested implementations.

Design, build, and operate scalable ETL/ELT pipelines and data platform capabilities to support analytics, AI/ML, and product needs. Lead technical designs, mentor engineers, implement DataOps/CI/CD and observability, ensure data quality/governance/security, and optimize performance and cost across cloud-based data systems.

Develop and design data pipelines, optimize data delivery and automate processes to support end-to-end solutions in various settings.

The role involves managing data infrastructure, building data pipelines, providing analytics to inform business decisions, and shaping AI workflows in the organization.

Design, build, test, deploy, and monitor batch and streaming data pipelines and ETL processes. Evaluate and adopt data technologies (including Adobe Experience Platform and CDPs), collaborate with data scientists, architects, and business partners to ingest and prepare large semi-structured/unstructured datasets for ML training, model execution, and search analytics, and implement automation, documentation, and tooling for scalable analytic data systems.

The IT Controls Data Engineer will create and maintain data pipelines and automated evidence workflows for IT controls, ensuring compliance and audit readiness.

Lead data engineering efforts, manage data governance, ensure compliance, and oversee data platform economics while designing scalable systems.

Design and own the companys end-to-end data and analytics stack: build metrics, dashboards, and reporting; instrument product and GTM signals; transform messy data into structured inputs for AI agents; and define analytics infrastructure (dbt, Snowflake, Mode) while partnering across founders, engineering, and GTM teams.

Design, build, and maintain systems and architecture to collect, store, and analyze large volumes of data in support of DoD/IC programs. Work with stakeholders to enable data ingestion, storage, and analytics pipelines.

Design, build, and deploy scalable data pipelines and validation for government production environments. Establish and maintain schemas, optimize SQL, handle messy/disparate data sources, work with large (100GB+) workflows, use Databricks/Spark/Python, and support ML/predictive solutions while mentoring teammates and engaging with clients. Active Secret Clearance required.

Design, build, and maintain scalable data pipelines and models for Finance and operations; collaborate with analysts and data scientists to provision trusted analytics; ensure governance, performance, testing, and incident root-cause fixes; recommend technologies and mentor team members to adopt cloud-first, best-practice data architectures.

As a Data Engineer at Booz Allen, you'll design and develop data pipelines, support data systems, and ensure data security while working in a team-focused environment.

Design, build, and operate enterprise-scale data pipelines and platforms (ETL/ELT) using Palantir Foundry and Databricks. Parse and process structured and unstructured data, develop scripts to convert data, mentor cross-functional teams, and monitor/scale data solutions for mission-driven analytics.

The role involves designing and building scalable data platforms, migrating data to the cloud, and implementing CI/CD practices while collaborating with cross-functional teams.

The role involves structuring and ingesting customer data, setting up ETL pipelines, and providing solutions for data export and import.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

Lead implementation of ETL patterns and reliable data infrastructure, partner with business and engineering teams to prioritize and deliver integrations, APIs, and reusable components, and support operational data applications in an Agile environment.

Design, build, and maintain an internal data platform and pipelines. Ensure secure, governed, resilient data access for engineering and BI teams. Partner with architects, implement automations, support platform consumption, mentor users, and drive continuous improvement and compliance.