Top Data & Analytics Jobs

Designs, develops, and maintains scalable data warehouses, data lakes, platforms, and ETL/ELT pipelines. Builds batch and streaming workflows, processes structured and unstructured data, optimizes cloud storage and pipeline performance, and implements data governance and lifecycle management. Guides multidisciplinary teams in agile environments while delivering mission-focused data engineering solutions.

Design, build, optimize, and operate scalable ETL/ELT pipelines supporting petabyte-scale legacy-to-cloud data migration. Develop data models, mappings, schemas, and data quality processes for structured and unstructured datasets. Improve automation, performance, reliability, and fault tolerance while supporting AWS security and compliance requirements. Collaborate with QA, Cloud, DevSecOps, and migration teams; document workflows; track migration progress; and mentor engineers. This is a full-time, on-site role in Huntsville, Alabama requiring active Top Secret clearance.

Build and maintain databases, data warehouses, and ETL/ELT pipelines for client data solutions. Consult with clients to translate technical needs into data architectures, ensure data quality and governance, optimize system performance, and support secure, compliant data integration. Collaborate with data integration engineers, business analysts, software engineers, and technical and non-technical stakeholders in a client-facing role.

Designs, builds, and operates scalable batch and streaming data pipelines on Databricks for federal missions. Responsibilities include developing Spark and Delta Lake solutions, managing clusters and workflows, implementing Unity Catalog governance and security, optimizing ETL/ELT processes, integrating CI/CD, supporting machine learning and advanced analytics, monitoring data quality, and collaborating with technical teams and stakeholders.

Develops geospatial and enterprise data solutions supporting national security analytics. Responsibilities include integrating and governing data, managing metadata and metrics, querying databases with SQL, accelerating large-scale transactions on GPU architectures, and applying Python data science and machine learning libraries. The role also produces assessments, briefings, reports, and intelligence products while coordinating projects, personnel, working groups, and cross-community stakeholders. An active TS/SCI clearance with SSBI is required.

Build and manage complex ETL and data pipelines, data warehouses, monitoring, and alerting systems for a legal-focused infrastructure team. Lead cross-functional data engineering initiatives from planning through delivery, optimize large-scale data processing, identify reliability issues, and communicate with technical and non-technical stakeholders. The role also involves supporting consulting practice activities, documentation, thought leadership, and client-facing deliverables.

Leads enterprise data engineering architecture and SAP data conversion initiatives. Designs scalable ingestion, transformation, storage, and delivery patterns; builds BODS ETL workflows; manages extraction, cleansing, mapping, validation, reconciliation, and loading. Establishes automation, governance, quality, lineage, security, observability, and infrastructure-as-code practices. Coordinates analysts, SAP teams, engineers, business owners, vendors, and consultants through mock conversions, cutovers, rollback, and production operations while coaching teams and resolving critical issues.

Develop and maintain software, data pipelines, ETL workflows, automation, and databases supporting SAPRO's mission. Use R, SQL, Python, and Databricks for data extraction, transformation, manipulation, and analytical workflows. Troubleshoot and optimize pipelines, enhance software, define technical requirements, and collaborate with technical and non-technical stakeholders. The role requires at least three years of data engineering experience and an active Secret clearance.

Build and maintain enterprise data pipelines and integration workflows across on-premises and cloud systems. Ingest, transform, and stage structured and semi-structured data; write and optimize SQL queries, views, and stored procedures; implement data validation, monitoring, alerts, and logging; document pipeline logic; manage source control and code reviews; and support data operations through ticket response and on-call rotations.

Build and maintain enterprise data pipelines and integration workflows across on-premises and cloud systems. Ingest, transform, and stage structured and semi-structured data; write and optimize SQL queries, views, and stored procedures; implement data validation, monitoring, alerts, and logging; document pipeline logic; use source control and code reviews; and provide support through tickets and on-call rotations.

Build and maintain production data ingestion pipelines, transformation models, warehouses, and schemas for PerfectServe’s data platform. Deploy reliable, tested pipelines using idempotency and data-quality checks, apply dimensional and medallion modeling, participate in design reviews, and document owned pipelines and runbooks. The role requires SQL, programming experience, dbt or similar transformation tools, cloud data warehouse experience, ELT orchestration, AWS knowledge, and a strong data-testing mindset.

Build and own marketing data, attribution, tracking, audience sync, and conversion infrastructure. Integrate product, CRM, warehouse, and advertising platforms; send offline conversions and LTV signals to ad platforms; maintain event schemas and dashboards; debug data discrepancies; implement privacy-safe tracking; and partner cross-functionally with growth, product, marketing, and data teams.

Designs, deploys, and optimizes production-grade data infrastructure, ETL/ELT pipelines, distributed databases, streaming systems, vector databases, APIs, and feature stores for AI and machine learning applications. The role also implements data quality, observability, lineage, testing, compliance, and secure cloud-native deployments. As a forward-deployed engineer, the employee partners directly with customers, prototypes solutions, transitions them to production, and feeds field learnings into platform improvements.

Designs, develops, and maintains scalable AWS data platforms, data lakes, and pipelines. Builds workflows with Glue, S3, Lambda, and Step Functions; implements governance and access controls through Lake Formation; automates infrastructure with Terraform; and develops Python and Boto3 integrations. Manages Snowflake platforms, CI/CD deployments, testing, monitoring, troubleshooting, and production optimization using CloudWatch and Splunk. Collaborates with engineering and architecture stakeholders while using AI-assisted development tools.

Build and deploy scalable data pipelines and platforms that organize structured and unstructured data. Responsibilities include ETL development, data platform design and maintenance, analytical exploration, database integration, automation, and collaboration with analysts, developers, data scientists, infrastructure engineers, and data consumers in agile, mission-driven environments.

Build and maintain Snowflake data models using dbt and orchestration tools, improve data quality and observability, define data contracts, and support a modular healthcare data platform. Collaborate with analysts, data scientists, and software engineers to deliver trusted datasets. Monitor and troubleshoot pipelines, optimize Snowflake performance and costs, participate in design reviews, document systems, and support governance, security, and privacy standards for healthcare data.

Build, test, document, and optimize Snowflake data models using dbt. Improve data quality, observability, lineage, and data contracts while collaborating with analysts, data scientists, and software engineers. Monitor pipelines, troubleshoot incidents, optimize query and storage performance, support client-specific configurations, participate in design reviews, and contribute to scalable data platform patterns. The role also requires clear documentation and awareness of security, governance, privacy, and healthcare data requirements.

Designs and maintains data visualization, reporting, and business intelligence platforms. Builds Python frameworks, dashboards, reporting applications, and analytics solutions for traders, quants, and developers. Optimizes data access and query performance, supports Looker, BigQuery, Plotly Dash, and Jupyter Notebooks, translates stakeholder requirements into technical solutions, and leads migrations across tools, libraries, and data sources.

Owns the architecture and evolution of enterprise-scale data ecosystems supporting global monitoring products. Responsibilities include designing high-availability pipelines, developing data strategies, building ETL/ELT solutions, maintaining CI/CD and automated QA, improving data performance, conducting technical design reviews, mentoring engineers, and collaborating with product and engineering leadership. The role focuses on cloud-native systems, customer-facing data products, geospatial datasets, and defense-related monitoring solutions.

Designs and maintains data pipelines, ELT processes, data warehouses, ingestion systems, and data models. Builds automated orchestration and integration components, ensures data integrity through monitoring and alerts, and documents data architecture. Collaborates with analysts, data scientists, and machine learning engineers while contributing to scalable, reliable data processing architecture across cloud and partner data sources.

Build and operate reliable data systems and products supporting clinical operations, drug evaluation, business development, analytics, machine learning, and AI agents. Responsibilities include designing pipelines, canonical data models, data contracts, warehouse transformations, quality and observability practices, governance for regulated data, and incident response. The role partners closely with Product Engineering and Data Science, uses AI-assisted development, contributes to architecture, and mentors other engineers.

Lead the design and delivery of scalable data solutions, including data pipelines, transformations, metadata frameworks, quality controls, and governance. Collaborate with stakeholders, product owners, and engineering teams to implement requirements, troubleshoot issues, test solutions, and improve engineering practices. Mentor junior engineers, lead proof-of-concepts, support CI/CD and automation, and ensure data architectures meet business and technical needs.

Own and scale the AI research data platform, including ingestion, processing, governance, versioning, lineage, quality, observability, and export for multimodal datasets. Build Databricks and distributed processing infrastructure, synthetic data generation pipelines, and self-service tools for ML researchers. Partner with security and compliance teams, mentor engineers, manage infrastructure automation, and establish the long-term platform roadmap.

Builds scalable ELT pipelines, data models, business metrics, and semantic layers supporting analytics, reporting, and AI/ML applications. The role ingests data into Snowflake, develops dbt and SQL transformations, validates data quality and governance, and partners with product managers, analysts, data scientists, visualization teams, and business stakeholders. Responsibilities include harmonizing media data, delivering ready-to-use datasets, and supporting strategic decision-making across television production, distribution, and marketing.

Build and maintain a near-real-time financial forecast dashboard using Flourish and Canva. Integrate Binance and Bloomberg APIs, automate financial modeling and data updates, translate complex metrics into visual narratives, and optimize dashboard accuracy and responsiveness. Collaborate with advertising, design, marketing, and analytics teams to ensure brand alignment and client-focused user experience.