Top Data & Analytics Jobs

Designs and deploys scalable data pipelines, preprocessing workflows, feature-engineering services, and machine learning models for secure DoD environments. The role supports structured and unstructured mission data, exploratory analysis, visualization, model inference APIs, reproducible MLOps workflows, and decision-support capabilities. Responsibilities include collaborating with product, software, platform, DevSecOps, data science, and mission teams; deploying containerized services; participating in Agile delivery; and maintaining technical documentation.

Design, develop, deploy, operationalize, and maintain enterprise-scale data applications, pipelines, and platforms. Process structured and unstructured data, build scalable ETL and ELT workflows, convert data into usable formats, and support monitoring and operation of data platforms. Collaborate with analysts, developers, engineers, and data consumers in an agile environment to deliver mission-driven solutions.

Designs and manages large-scale structured and unstructured data pipelines in AWS. Builds RAG pipelines involving document ingestion, embeddings, indexing, and retrieval; orchestrates ETL/ELT workflows with Prefect and Apache NiFi; and optimizes Elasticsearch systems. The role supports analytics, ML, and application workloads while ensuring data quality, governance, lineage, security, observability, and reliability. Collaboration with architecture, ML, and application teams and troubleshooting distributed systems are also required.

Designs and maintains scalable data pipelines using Databricks, Spark, and cloud services. Builds transformation workflows, integrates APIs, databases, and cloud storage, and supports analytics and reporting. Implements data validation, monitoring, observability, governance, security, and automation. Collaborates with data science, analytics, and business teams to deliver reliable data solutions in AWS and other cloud environments.

Build and maintain secure, scalable data pipelines, ETL/ELT processes, data models, curated datasets, and analytics-ready data products. Ensure data quality, governance, reliability, monitoring, and production support while collaborating with analysts, data scientists, engineers, and business stakeholders. Support marketing, customer analytics, reporting, machine learning preparation, and continuous improvement through testing, documentation, code reviews, and deployment activities.

Design and implement scalable data pipelines and a SOC2-compliant data warehouse. Support analytics and ML teams, enable real-time and batch ETL, mentor data engineers, and collaborate cross-functionally to drive data-driven decisions.

Supports the development, maintenance, and monitoring of scalable ETL/ELT data pipelines in secure environments. Responsibilities include ingesting, cleaning, transforming, and validating structured and unstructured data; working with relational and NoSQL databases; building Docker modules; performing security scans and unit tests; and participating in Agile ceremonies and code reviews.

Architects and leads enterprise-scale data platforms, data mesh topologies, lakehouse infrastructure, and real-time analytics for classified environments. Establishes data architecture strategy, security and encryption standards, zero-trust governance, multi-cloud and air-gapped deployment strategies, and enterprise data modeling practices. Serves as the principal technical authority and advises government and executive stakeholders on mission-critical data capabilities.

Leads architecture, scaling, governance, and implementation of enterprise data platforms across multi-cloud and air-gapped environments. Designs batch and streaming systems, optimizes Spark and Trino/Presto clusters, implements Terraform-based infrastructure, establishes data quality, lineage, security, and compliance controls, and leads Agile engineering pods while mentoring staff. Requires advanced expertise in distributed data systems, cloud platforms, Kubernetes, programming, and regulated defense environments.

Design, build, and operate scalable real-time and batch data pipelines ingesting high-frequency telemetry, simulation, and trackside data. Own Kafka/Flink streaming components, Databricks lakehouse implementations, and infrastructure-as-code deployments. Develop software in Python/Java/SQL, integrate systems, automate testing and releases, performance-tune pipelines, and mentor peers to ensure resilient, secure, high-performance data delivery for motorsports teams.

Leads enterprise data engineering by architecting Snowflake and dbt platforms, scalable pipelines, data models, governance, observability, and integrations. Partners with business, architecture, compliance, and technology teams to deliver reliable data products. Resolves complex production issues, improves data quality and performance, supports AI/ML data infrastructure, and mentors engineers while establishing engineering standards and technical direction.

Build the company’s foundational data platform, including ETL/ELT pipelines, ingestion from databases, SaaS tools, and APIs, a cloud data warehouse, transformation models, data quality checks, observability, documentation, and monitoring. Collaborate with Product, Operations, Finance, Analytics, and Engineering stakeholders to create durable datasets and support a production data stack.

Designs and deploys end-to-end data infrastructure, including schemas, warehouses, automated pipelines, data quality monitoring, and curated datasets. Builds Power BI solutions for self-service analytics and partners with product, marketing, sales, data science, and machine learning teams. Applies analytical techniques, productionizes machine learning and LLM use cases, and translates complex data into business insights.

Designs, builds, and maintains scalable data pipelines and integration solutions using Kafka, Elastic Stack, AWS, and OpenShift. Integrates network operations data, develops ETL/ELT processes, data lakes, warehouses, dashboards, and CI/CD automation. Optimizes ingestion, query, indexing, storage, and cluster performance while ensuring data quality, security, and DoD compliance. Collaborates with analysts, visualization engineers, end users, and support teams to deliver documented, actionable data solutions.

Lead pre-sales technical engagements to design and optimize scalable cloud lakehouse data platforms (Snowflake/Databricks). Provide architecture reviews, ETL/ELT pipeline design, governance and AI-ready data foundations, support services sales, and translate technical tradeoffs into actionable recommendations for engineering and executive stakeholders.

Design, build, and own scalable ETL/ELT pipelines, data models, and data infrastructure. Improve data quality, observability, performance, and CI/CD for data workflows. Partner with analytics, ML, software, and product teams, mentor engineers, and resolve complex data issues.

Lead cross-functional Agile teams to design, build, test, and support cloud-based data solutions. Develop full-stack data engineering systems using Java/Scala/Python, RDBMS and NoSQL, Redshift/Snowflake, and distributed tools (Hadoop, Spark, Kafka). Mentor engineers, perform code reviews and unit testing, and collaborate with product managers to deliver scalable, performant data products.

The Senior Lead Data Engineer designs and develops technical solutions, leads a team of developers, and utilizes big data and cloud technologies to deliver robust solutions for Capital One.

Lead a team of engineers to design and implement data solutions using cloud technologies, optimizing data pipelines and collaborating with Agile teams to deliver impactful data-driven products.

Lead and mentor data engineering teams to design, build, test, and support cloud-based, full-stack data solutions. Work with big data, streaming, and data warehousing technologies (Redshift/Snowflake), collaborate with product managers, and ensure high-quality, performant code and systems.

Lead Data Engineer designs, develops, tests, and supports cloud-based data solutions. Collaborates with Agile teams, mentors engineers, implements big data and streaming systems, and optimizes code for performance to deliver data-driven products.

Design, build, and maintain scalable batch and real-time data pipelines and data lake architecture. Improve observability and SLOs, optimize ETL/ELT, develop dbt workflows, support event-driven architectures, integrate financial APIs, and collaborate with analytics and ML teams to deliver reliable, model-ready data products.

Scope, implement, validate, and monitor merchant data integrations to ensure accurate input to data science models. Maintain data configuration, create JSON/CSV templates, write Python/SQL/Spark/Databricks/R scripts for testing and transformation, upload historical data, triage alerts, and coordinate with internal and client teams to resolve data issues and improve pipelines.

Design, build, and maintain scalable data pipelines and cloud data infrastructure (warehouse, RBAC, validation). Collaborate with data scientists and engineers, orchestrate ML pipelines, ensure data quality/security, optimize cost and performance, lead incident response and mentor teammates.

Build and maintain scalable data platforms and pipelines that organize structured and unstructured data. Retrieve, merge, analyze, and prepare data from APIs and databases for AI and GenAI models. Collaborate with analysts, engineers, developers, and data consumers in an agile environment while supporting data architecture, ETL, analytics, and machine learning initiatives for mission-driven clients.