Top Data & Analytics Jobs

Build Reducto’s data infrastructure from the ground up, owning warehouses, databases, pipelines, orchestration, transformations, data modeling, reliability, testing, freshness, and lineage. Integrate product, sales, and finance data into trusted company-wide datasets. Partner with Engineering, Finance, Operations, and GTM leaders to define business metrics and priorities. As the founding data hire, establish scalable architecture and standards while supporting analytics and business decision-making.

Leads enterprise logistics data architecture, data warehousing, ETL pipelines, data governance, and Power BI/Tableau visualization solutions. Partners with stakeholders and vendors to define data requirements, optimize models and cloud costs, automate reporting, and support Tyson transportation operations. Mentors junior engineers and interns while ensuring data security, privacy, quality, and effective resolution of complex escalations.

Develop and maintain scalable data platforms, data stores, and ETL/ELT pipelines that organize structured and unstructured data for analytics and mission-focused applications. Collaborate with analysts, developers, data scientists, infrastructure engineers, and data consumers in agile teams. Create scripts and programs to transform data, support platform operations, and deploy batch and streaming analytics solutions. The role requires Python, a Secret clearance, and a bachelor's degree.

Designs, implements, and operates data management systems supporting defense intelligence requirements. Responsibilities include developing data architectures, optimizing data throughput and query performance, selecting backend database technologies, and integrating data across systems. The role also requires administering Linux and Windows server environments, VMware or Citix infrastructure, storage, backups, security baselines, LDAP accounts, and PKI authentication. An active Top Secret/SCI clearance with polygraph is required.

Leads enterprise data engineering and architecture initiatives, including cloud cost optimization, data governance, security, streaming, ETL, pipeline orchestration, and visualization. Guides data strategy, vendor relationships, escalations, architecture reviews, stakeholder collaboration, and team mentorship. Requires advanced SQL, data streaming, big data, scalable architecture, security, and visualization expertise, with five or more years of experience.

Designs and delivers scalable data pipelines, models, repositories, dashboards, and reporting solutions. Partners with business and technology stakeholders to translate requirements into technical solutions, supports ETL/ELT processes, ensures data quality and performance, leads projects, mentors team members, and promotes automation and continuous improvement across Guardian Pharmacy’s data platform.

Develop and implement client data systems, including database environments, data migration processes, and secure, efficient data access solutions. Contribute to data-system planning for stakeholder approval and collaborate directly with clients on projects. The role requires travel and/or relocation to unanticipated U.S. locations based on client and project needs. Technologies include Talend Enterprise Edition, ETL, Java, SQL, and PL/SQL.

Develop and maintain data lake and data mart architecture, translate client requirements into migration plans, extract and migrate data while preserving integrity and security, and create data visualizations. Collaborate with QA teams to resolve defects and validate systems. The role requires working with ETL, SQL, Oracle, Informatica, Teradata, and Power BI, plus travel or relocation to client project locations across the United States.

Design, develop, and deploy end-to-end real-time streaming and ETL/ELT solutions on AWS (including geospatial pipelines). Build APIs, implement infrastructure-as-code, ensure security/compliance, and move systems to production and O&M for high‑scale distributed environments.

Data Engineer supporting a United States Air Force program. Responsibilities include designing ETL pipelines, data warehouses and lakes, APIs, data quality controls, metadata and lineage practices, analytical datasets, security controls, automated deployments, monitoring, troubleshooting, and technical documentation. The role collaborates with government stakeholders, mission partners, technical teams, and data scientists while maintaining compliance with approved architectures, governance standards, and security boundaries.

Develop and maintain logical and physical data models, architectures, schemas, pipelines, and ETL processes. Ensure data governance, compliance, integration, reuse, and quality. Analyze data requirements, create decision-support materials, and brief senior leaders. The role requires extensive experience in data engineering, ORSA, data science, warehousing, ingestion, profiling, SQL, pandas, Python, and distributed data environments, along with an active TS/SCI clearance.

Lead administration and strategic evolution of a petabyte-scale Snowflake data warehouse supporting more than 900 users. Responsibilities include platform reliability, incident response, security and governance, monitoring, automation, schema migration, cost optimization, data quality, and compliance. The role partners with data and analytics teams, evaluates technologies, leads architecture reviews, and mentors engineers on Snowflake administration and data warehouse best practices.

Build and maintain scalable batch, streaming, and real-time data pipelines, platforms, data lakes, warehouses, and lakehouses. Implement data quality, governance, security, observability, automation, and cloud modernization. Partner with product, engineering, analytics, data science, and business teams to deliver analytics, AI/ML, reporting, and customer insight solutions. Troubleshoot production issues, guide architecture, mentor engineers, and provide technical leadership across marketing data initiatives.

Designs, builds, and operates production data pipelines on Databricks and Azure using Python, SQL, Spark, Delta Lake, dbt, and Dagster. Responsibilities include ingestion, medallion-layer transformations, dimensional modeling, ML datasets, data contracts, quality testing, governance, CI/CD, observability, performance tuning, troubleshooting, and on-call support. The role partners with architects, analysts, product owners, and business stakeholders to deliver reliable, reusable data products.

The Senior Data Engineer designs, develops, and operates scalable data warehouses, ETL/ELT pipelines, integrations, and data-quality frameworks. The role transforms data from internal and third-party systems into reliable, accessible resources for analytics and reporting. Responsibilities include automating data preparation, monitoring pipeline performance, improving data infrastructure, collaborating with stakeholders and IT, and providing technical guidance within an agile team.

Design, build, and operate production data pipelines using Python, Spark SQL, and Airflow. Canonicalize healthcare and customer data into trusted internal models, optimize distributed processing, enforce schemas, and implement quality checks and observability. Support customer onboarding, streaming pipelines, troubleshooting, on-call operations, and platform best practices while collaborating with product, analytics, engineering, data science, and customer teams.

Own the analytics data layer by translating stakeholder needs into certified dimensional models, governed metrics, semantic layers, dashboards, and reports. Build with dbt, SQL, Databricks, Power BI, and Airflow while ensuring data quality, observability, reconciliation, documentation, and dependable orchestration. Partner closely with finance, operations, and client-facing teams, automate recurring workflows, and use AI-assisted engineering practices in a fully remote environment.

Build and operate data platform services, APIs, SDKs, schemas, validation tools, event-driven pipelines, and reverse ETL workflows. Improve Kafka-based data delivery, schema evolution, observability, lineage, access controls, privacy, and compliance. Partner with engineering, analytics, data science, security, and infrastructure teams to create reliable, self-service data workflows. Operate AWS services, infrastructure as code, monitoring, alerting, and incident response.

Build and operate enterprise integrations and production data pipelines across Salesforce, NetSuite, Workday, Snowflake, and other business systems. Responsibilities include API-led integrations, SQL and Python transformations, data modeling, order-to-revenue workflows, testing, monitoring, data quality, security controls, and production support. Own projects end to end, partner with stakeholders, mentor engineers, and establish reusable engineering practices.

Own the technical design and operation of Palmetto’s governed data platform. Build trusted data products, semantic models, ingestion and transformation pipelines, secure access interfaces, and agent-ready data services. Establish governance, masking, authorization, observability, CI/CD, and audit readiness. Partner with finance, operations, product, and engineering teams while mentoring engineers and setting cross-team technical direction.

Develop and support SAP BRIM data migration solutions using BODS and EMIGALL. Responsibilities include source-to-target mapping, ETL development, data cleansing, validation, reconciliation, migration testing, SAP integrations, SQL analysis, production support, documentation, and cutover activities. The role collaborates with architects, functional consultants, infrastructure teams, and business stakeholders while supporting SAP S/4HANA, FICA, billing, and customer account migrations.

Build and support AWS data lake and Snowflake solutions, develop Python and Spark data pipelines, automate infrastructure with Terraform, and manage CI/CD deployments. The role uses AWS services including Glue, S3, Lambda, Step Functions, and Lake Formation, along with monitoring and change-management tools. Candidates will also apply AI-assisted engineering tools to improve productivity and may work with Databricks, Unity Catalog, and cloud analytics platforms.

Leads the design, development, and operation of scalable enterprise data products using Databricks and modern data engineering practices. Provides hands-on technical leadership across architecture, implementation, testing, troubleshooting, production readiness, observability, governance, and performance. Partners with architects and product teams to deliver analytical, operational, reporting, and AI-driven solutions. Establishes engineering standards, promotes responsible AI-assisted development, mentors engineers, and improves platform reuse and productivity.

Designs and maintains automation for enterprise data governance, including APIs, ETL pipelines, metadata management, data profiling, validation, quality workflows, and data integrations. Develops reliable scheduled and event-driven solutions with monitoring, logging, retry logic, testing, CI/CD, and exception handling. Collaborates with stakeholders on governance roadmaps, tool requirements, and scalable data management improvements.

Build scalable data ingestion, transformation, and loading infrastructure using Spark, SQL, AWS, and Databricks. Develop entity resolution systems, CI/CD pipelines, anomaly detection, and high-quality data products. Design scalable processing and storage patterns, orchestration workflows, and data warehousing solutions while collaborating remotely and documenting technical designs.