Top Data & Analytics Jobs

Designs and develops Databricks and cloud-based data solutions, reliable data pipelines, automated testing, and governed datasets. Collaborates with data scientists, product partners, architects, and engineers to deliver scalable analytics solutions. Responsibilities include mentoring junior engineers, improving data engineering practices, participating in Agile planning and retrospectives, and ensuring data quality, metadata documentation, and downstream usability.

Design and architect scalable healthcare data systems, core data models, and production data pipelines. Integrate and normalize healthcare data using TUVA, OMOP, and FHIR standards; establish data quality and governance; optimize performance; deploy secure cloud infrastructure; ensure regulatory compliance; and build bi-directional EMR integrations. The role also requires independent technical decision-making, test automation, CI/CD, and DevOps practices in a fast-paced healthcare technology startup.

Build and scale secure data lakehouse and warehouse infrastructure supporting analytics, machine learning, clinical AI performance monitoring, and self-service insights. Develop scalable data pipelines, models, orchestration, quality controls, and LLM-enabled analytics tools using heterogeneous clinical and EHR data. Collaborate with engineering, data science, clinical, product, and client success teams to establish trustworthy metrics and technical solutions.

Lead design and delivery of major Azure-based data systems and production-grade pipelines. Build semantic models, support BI and ML workloads, drive platform architecture and standards, mentor engineers, and solve performance, reliability, and scalability challenges across Fabric, Synapse, Power BI, and broader Azure services.

Design and deliver major Azure-based data systems and products (ingestion, transformation, storage, semantic modeling). Build production-grade pipelines and feature infrastructure for analytics and ML, drive platform architecture and standards, diagnose performance and scalability issues, mentor engineers, and partner with stakeholders to translate business needs into scalable data solutions.

Develops and tests Databricks data pipelines using SQL, Python, and Spark across bronze, silver, and gold medallion layers. Implements governance tagging, metadata standards, column masking, row-level security, access controls, and YAML-based configuration. Performs data quality validation and maintains data contracts for pilot, proof-of-concept, and production workflows. Requires collaboration across stakeholders and support for federal consulting clients handling controlled information.

Develops and supports Allegheny College’s enterprise business intelligence environment, initially focused on Oracle Fusion Data Intelligence. Responsibilities include data integration, SQL and ETL development, data modeling, dashboards, reporting, validation, troubleshooting, security, governance, documentation, user consultation, and analytics support. The role collaborates with functional departments and enterprise systems teams to translate reporting needs into secure, scalable solutions and contributes to institutional data modernization and decision-making.

Sustains and optimizes SSIS packages, develops SQL- and Python-based integrations, builds incremental data pipelines, manages APIs and schema changes, reconciles data, maintains lineage, troubleshoots failures, and supports testing, deployment, documentation, and secure data operations for a government mission.

Leads the design, development, optimization, and maintenance of enterprise ETL and data integration pipelines. Maintains SSIS, develops SQL and Python automation, implements APIs and incremental loads, and builds raw, standardized, and curated data layers. Establishes reconciliation, lineage, retry, recovery, schema-change, and failed-record processes while monitoring pipeline health and troubleshooting complex issues. Provides technical leadership, code reviews, documentation, stakeholder communication, and mentoring in a secure federal data environment.

Designs and maintains data models, metadata, ETL processes, warehouse components, dashboards, reports, and visualizations for a government program. Translates requirements into data transformations and reporting logic, validates data quality and outputs, optimizes performance, supports testing and deployment, coordinates system changes, and maintains technical documentation, lineage, and operational handoffs. Collaborates with engineers, database administrators, analysts, testers, governance teams, and government stakeholders.

Designs and implements data governance, metadata, tagging, security, and access-control solutions in Databricks and Unity Catalog. Defines governance across Bronze, Silver, and Gold medallion layers, including masking and row-level security. Develops scalable SQL and Spark pipelines, evaluates architecture decisions, and establishes declarative data contracts. Collaborates with technical teams, data owners, security stakeholders, and business partners. The remote role requires occasional travel and U.S. citizenship, with Public Trust or suitability determination eligibility.

Develops and deploys scalable big data platforms, ETL pipelines, data warehouses, and data architectures. Designs, codes, tests, documents, and optimizes data solutions; troubleshoots data issues; improves reliability, efficiency, and quality; and collaborates with developers, architects, analysts, scientists, and business teams.

Designs and builds scalable batch and real-time data pipelines, ingestion workflows, analytical systems, data products, and intelligent APIs. Ensures data quality, reliability, and performance while supporting cloud-based data architecture for BI and AI/ML use cases. Collaborates with cross-functional teams, participates in code reviews, and follows DevOps and CI/CD practices using Databricks, Spark, Python, SQL, and Azure services.

Build, scale, and optimize ETL and ELT data pipelines using Databricks, PySpark, Python, SQL, and distributed processing technologies. Collaborate with data engineering, AI, governance, and reporting teams to support analytics and reporting outcomes. Contribute to cloud data architecture, AI integration, DataOps, MLOps, and modern data platform capabilities including Unity Catalog, workflows, notebooks, medallion architecture, and Delta Lake.

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.

Collaborate with data engineering and business teams to onboard data sources, define KPIs, and develop scalable MicroStrategy reports, dashboards, and BI applications. Design logical data models, optimize SQL and BI platforms, validate reporting accuracy, support governance, document solutions, and provide user training and technical support. Work with cloud data platforms, data warehouses, and data scientists to support analytics and outcome measurement.

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.