Top Data & Analytics Jobs

Develop and optimize SAP Data Services ETL/ELT workflows integrating SAP and non-SAP systems. Create source-to-target mappings, extraction routines, transformations, data quality processes, and profiling solutions. Monitor and troubleshoot jobs, tune SQL and database performance, and apply SAP HANA optimization techniques. The role requires collaboration across functional and technical teams while supporting a mission-critical Department of Defense transportation and logistics environment.

Designs, develops, deploys, and supports scalable batch and streaming data pipelines, lakehouse solutions, warehouses, and governed data products. The role uses AWS, Spark, orchestration, data modeling, quality controls, security, DevSecOps, and data mesh practices to support analytics, BI, data science, and AI. It also provides technical leadership, manages risks and dependencies, partners with business and technology teams, and owns solutions through production operations and continuous improvement.

Designs and leads production-grade batch, incremental, streaming, and real-time data pipelines across Microsoft Fabric and Azure. Builds Delta Lake medallion architectures, dimensional and Data Vault models, CDC and incremental-loading solutions, CI/CD automation, governance, security, observability, and data-quality controls. Supports migrations to Fabric, prepares governed data for AI and RAG workloads, and leads client-facing engineering workstreams, estimates, risk management, mentoring, and operational handover.

Own PushPress’s data platform, including ingestion, orchestration, cloud warehouse performance, governance, privacy, data quality, monitoring, and AI-ready data foundations. Build reliable pipelines integrating product, payment, and third-party data; establish data contracts, access controls, auditability, and semantic definitions; support real-time analytics and trustworthy reporting. Partner with Engineering, Data, and AI teams while maintaining infrastructure, incident response, documentation, and operational runbooks.

Build governed data models, tested analytics transformation layers, ETL pipelines, semantic datasets, and AI-ready data workflows. Partner with analysts, developers, and domain experts to define metrics, schemas, documentation, lineage, and validation frameworks. Support ML features, retrieval pipelines, unstructured data, and LLM output benchmarking while applying software engineering, compliance, and performance standards.

Designs and maintains scalable data pipelines, models, warehouses, lakehouses, and cloud-based data platforms. Builds ETL/ELT workflows, supports AI/ML data needs, implements data quality and governance controls, and manages batch and streaming integrations. Collaborates with technical and business teams to deliver reliable data solutions, troubleshoot infrastructure, and improve scalability, performance, and business value.

Design, build, and operate large-scale ETL pipelines, data lakes, and data platforms processing billions of daily events. Own data quality, freshness, reliability, monitoring, and observability for foundational datasets. Develop self-service ETL frameworks and tooling, contribute to architecture and technical strategy, and partner with product, engineering, machine learning, data science, and leadership teams to deliver scalable data solutions.

Develops and maintains production data pipelines, ETL/ELT workflows, data solutions, and ML infrastructure using Python, AWS, and related technologies. Responsibilities include data ingestion, transformation, validation, storage, monitoring, troubleshooting, performance optimization, and deployment. Collaborates with data scientists, analysts, product teams, and stakeholders in an agile environment.

Build and own production data infrastructure for a healthcare AI platform. Responsibilities include REST API ingestion, Azure Event Hubs streaming into Databricks, Delta Lake medallion pipelines, entity resolution, semantic metrics, data-quality instrumentation, reconciliation, schema-drift handling, and troubleshooting source-to-warehouse discrepancies. The role requires strong Python and SQL skills, independent pipeline ownership, and experience with Databricks, Spark, PySpark, streaming, and healthcare-related data is a plus.

Develop and maintain enterprise geospatial applications, web services, dashboards, geoprocessing tools, and automation using Python and Esri technologies. Integrate and administer geospatial systems, troubleshoot GIS applications, manage data gateways, and migrate legacy applications to AWS Cloud One. The role also requires ArcGIS administration, database experience, spatial data standards knowledge, technical communication, and support for Air Force GeoBase initiatives using Agile practices.

Designs and builds lakehouse data models, pipelines, data marts, semantic layers, and digital-twin integrations for power plant assets. Combines telemetry, financial, operational, maintenance, and reliability data using Azure and Databricks technologies. Develops visualizations and supports web-product delivery while collaborating with product managers, UX designers, software engineers, analysts, plant staff, and executives.

Build and optimize scalable ETL/ELT pipelines using Matillion, AWS, and Snowflake. Develop governed, certified Data Products for an enterprise Data Marketplace across bronze, silver, and gold data layers. Implement data quality, lineage, metadata, access controls, CI/CD, monitoring, and certification workflows. Collaborate with analysts, data scientists, AI/ML teams, product owners, and stakeholders; contribute to architecture, roadmap planning, code reviews, mentorship, and reusable engineering practices.

Build and manage dbt data pipelines, canonical datasets, dashboards, reporting, and foundational data products. Partner with Product, Engineering, and cross-functional teams to define reliable metrics, data models, technical requirements, and analytics systems for consumer products. Establish data integrity standards and SLAs, enable self-service analytics, and influence Product roadmaps through data architecture expertise.

Designs and maintains production data pipelines, models claims and operational data, and improves reliability through testing, monitoring, and alerting. Owns workflow troubleshooting, backfills, performance optimization, documentation, access controls, and CI/CD practices. Partners with business and technical teams to define requirements and deliver trusted datasets using SQL, Python, cloud data warehouses, and orchestration tools.

Design and implement scalable data infrastructure, pipelines, integrations, and models. Build automated insurance reporting pipelines, unify siloed datasets, enable self-service analytics, and enforce governance, quality, security, testing, and reliability standards. Partner with Risk, analytics, product, and cross-functional teams to deliver data solutions using modern data engineering tools and practices.

Build and maintain scalable data platforms, ETL and ELT workflows, and pipelines for structured and unstructured data. Develop software and scripts to retrieve, parse, process, and transform data for reporting and analytics. Support secure information management systems, monitor and operate data platforms, and collaborate with analysts, developers, engineers, and data consumers in an agile environment.

Design and maintain a centralized SQL Server database, data model, and Python/SQL ETL pipelines integrating business systems such as NetSuite, Arena, ION, and Jira. Build Power BI dashboards and KPI reports, support NetSuite customizations, and partner with cross-functional teams to deliver integrations and technical solutions. The role also promotes data quality, governance, documentation, and change control.

Build and optimize real-time and batch data pipelines, integrations, data warehouses, ETL processes, and reconciliation systems. Develop complex SQL queries, APIs, analytic reports, and data tools while supporting production pipelines and troubleshooting data integrity issues. Partner with architects, analysts, developers, and cross-functional teams to improve data reliability, quality, scalability, and accessibility across cloud and on-premises environments.

Design and implement scalable data solutions using Microsoft Fabric and Azure. Build and orchestrate ETL/ELT pipelines, develop Power BI reports and DAX, optimize T-SQL and KQL queries, model data for Lakehouse/warehouse architectures, integrate varied data sources with Spark/PySpark, automate processes, ensure governance and security, and troubleshoot pipeline issues.

Participate in the Gradient Development Program through structured training, hands-on technical work, mentorship, and certification preparation. Collaborate with technical and business leads to translate business requirements into effective solutions. The program prepares recent graduates for technology consulting careers and future delivery consultant responsibilities.

Designs, develops, and maintains Snowflake data pipelines using Matillion for analytics and business intelligence. Responsibilities include ETL/ELT development, database optimization, data modeling, governance, quality assurance, documentation, troubleshooting, and integration of structured and unstructured data. The role uses Python, SQL, and PowerShell, collaborates with business and technical stakeholders, supports reporting initiatives, and evaluates emerging data technologies.

Designs trusted Snowflake data products and enterprise semantic models that standardize business concepts, metrics, relationships, and rules. Builds Cortex semantic views and agents, validates AI-generated results, develops regression tests, and maintains metadata, lineage, and documentation. Leads modeling initiatives from discovery through production while partnering with business and technical stakeholders to improve analytics, automation, and AI consistency.

Builds and maintains cloud data pipelines, transformations, semantic views, conformed dimensions, and analytical data models. Implements data quality controls, lineage, documentation, testing, release-readiness evidence, and defect resolution. Collaborates with data owners, governance teams, engineers, security stakeholders, data scientists, and customers to deliver reliable, governed data products supporting analytics, reporting, self-service BI, and AI/ML use cases.

Designs and optimizes scalable ELT/ETL pipelines using dbt, SQL, Snowflake, and Azure. Leads data architecture, dimensional modeling, performance tuning, CI/CD, data quality, observability, lineage, governance, and security. Partners with stakeholders to create reliable analytics assets, evaluates GenAI applications, mentors junior engineers, and supports modern cloud data operations.

Own developer relations for GPU-accelerated analytical data processing: integrate NVIDIA libraries into query engines and OLAP databases, produce rigorous benchmarks, create reference integrations and guides, collaborate with engine architects and NVIDIA product teams to define APIs and roadmap, and drive adoption across open source and commercial projects.