Top Senior Data Engineer Jobs

The Senior Data Engineer will design, build, and maintain scalable party data solutions, integrating cloud-native platforms and improving legacy systems while mentoring junior engineers.

Design, build, and operationalize data and ML pipelines on Databricks. Implement CI/CD and infrastructure-as-code, ensure data quality/governance, troubleshoot incidents, and collaborate cross-functionally to enable reproducible ML lifecycle and deployments.

Lead and mentor multiple Databricks-focused data engineering teams, define engineering best practices and reusable frameworks, drive CI/CD and performance/cost optimization, build and support analytical and streaming pipelines, and collaborate with architects, product owners, and cross-functional partners to deliver high-quality data products.

The Data Engineer will design and optimize ETL pipelines, integrate data, ensure data quality, and troubleshoot issues, enabling decision-making across the organization.

Lead the architecture and design of data and analytics solutions, focusing on ETL, data warehousing, and cloud technologies while collaborating with global teams to optimize data processes.

As a Data Engineer, you will design and build scalable data pipelines and models, maintain data governance, and collaborate with AI engineers while ensuring data quality and compliance.

Design and implement large-scale Snowflake-based data platforms, migrate on-prem databases to AWS/Snowflake, build ETL/ELT pipelines and data lakes, create dimensional models, maintain CI/CD and scheduling (Control-M), provide technical leadership and modernization guidance, and develop performant data solutions across multiple database platforms.

The Data Engineer will design and maintain data models on Snowflake, enforce data standards, manage security, optimize SQL, implement CI/CD, and mentor junior staff.

Lead the development of AI data pipelines, improve data capabilities, integrate AI solutions, mentor team members, and ensure operational efficiency.

The HR Data Engineer designs and maintains data pipelines, transforms HR data into insights, and ensures data accuracy, governance, and security while supporting analytics initiatives.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Design, build, and maintain scalable ETL/data pipelines and data models; ensure data quality and governance; collaborate with data scientists, analysts, and stakeholders; optimize performance and document data systems; evaluate and adopt data platform technologies.

Own and evolve the data platform by leading architectural evolution, collaborating with teams for strategic data initiatives, and ensuring reliable data systems.

Lead design and delivery of scalable data integration, storage, and infrastructure to enable analytics and AI. Build ETL/ELT pipelines, cloud-native data systems, IaC and CI/CD, ensure SRE practices (SLOs/SLIs), prototype end-to-end solutions, and drive architectural trade-offs while collaborating across teams to transition validated solutions to platform engineering.

Design, develop, and maintain AxiomSL data sources, mappings, and regulatory reports. Build scalable data pipelines, perform advanced SQL transformations, ensure data lineage and reconciliation, support audits and production L2/L3 operations, and drive automation and platform upgrades to meet regulatory requirements.

The Data Engineer conducts data analytics projects, implements data standards, and collaborates with stakeholders while ensuring data quality and integrity.

The Cloud Data Engineer will design, implement, and manage data solutions on Microsoft Azure, create and maintain data pipelines, and ensure data security for decision-making processes.

Lead technical onboarding and integrations: map customer schemas to canonical models, design incremental and full data syncs, deploy pipelines across on-prem/cloud infra, collaborate with AI/ML teams to ensure high-fidelity inputs, and own successful customer deployments and last-mile onboarding.

Build and optimize core data platform: improve ClickHouse performance, create configurable ingestion schemas, develop shared Python libraries, design integration pipelines, and architect monitoring/observability for reliable, production-grade data delivery.

Design, build, and operate GTM data pipelines, a unified data lake, and enrichment workflows using cloud data infra, LLMs, and orchestration tools to enable segmentation, ICP scoring, and revenue analytics.

The Lead Data Platform Engineer will design and build Virtuous's data platform, ensuring it is secure, scalable, and AI-ready. Responsibilities include architecting access controls, optimizing performance, and enabling self-service analytics while maintaining governance and compliance standards.

Senior Data Engineer responsible for designing, building, and operating scalable Databricks-on-AWS data pipelines, implementing CI/CD and IaC, ensuring data quality and governance, and mentoring junior engineers to support analytics and ML workloads.

The Senior Data Engineer will lead data discovery for USSOCOM, managing tools like BigID and NetApp BlueXP to enhance data visibility and classification in hybrid environments.

Design, develop, and maintain large-scale data architectures and pipelines; deploy cloud-native data applications and CI/CD; support ML model productization; enforce code hygiene and best practices; mentor junior engineers; produce documentation and runbooks; collaborate with consulting teams and clients and travel as required.

The Data Engineer will build and operationalize data solutions, design complex data systems, collaborate across teams, and ensure high-quality data management.