Top Senior Data Engineer Jobs

Designs, builds, and operates production data pipelines supporting AI-enabled engineering workflows. Owns data curation, indexing quality, pipeline reliability, schemas, governance, metadata, lineage, and data-quality controls. Partners with AI, IT, and engineering teams to integrate systems such as Windchill, Jira, GitLab, and AWS. Supports retrieval-augmented generation, agentic workflows, evaluation harnesses, and production scaling in a regulated medical-device R&D environment.

Leads enterprise data integration and engineering capabilities, including APIs, middleware, ELT pipelines, data governance, master data management, and cloud analytics platforms. Designs secure, compliant integrations across ERP, CRM, clinical, research, quality, finance, and commercial systems. Establishes architecture standards, data quality controls, monitoring, validation, and support processes while coordinating internal engineers, vendors, and business stakeholders. The role also provides technical leadership for trusted datasets, regulatory compliance, operational reliability, and commercialization readiness.

Leads data engineering strategy, architecture, delivery, support, and lifecycle management for secure, scalable cloud and hosted data solutions. Collaborates with technical and business stakeholders to deliver complex datasets, establish enterprise data standards, manage data engineering teams, and oversee maintenance, change management, capacity planning, business continuity, disaster recovery, and regulatory security requirements. The role also evaluates third-party tools and supports Azure DevOps, SDLC, CI/CD, and technical innovation.

Leads data engineering for Payment Operations monitoring transformation. Designs and maintains Snowflake pipelines, tables, stored procedures, monitoring scenarios, KPI infrastructure, and data quality controls. Serves as the Snowflake subject matter expert, documents architecture and operational processes, guides technical partners, and translates business needs into scalable data solutions. The role requires production data engineering experience, advanced SQL, Snowflake expertise, job scheduling, pipeline operations, and stakeholder communication.

As a Senior Data Engineer, you will design, build, and maintain scalable data platforms, ETL pipelines, and support analytics and ML workflows, ensuring data quality and cross-functional collaboration.

The role involves designing and implementing ETL solutions for data integration, conducting testing, and collaborating on data models and architecture documents for a client.

The Senior IT Big Data Developer will design and optimize data architectures, develop ETL/ELT pipelines, support data integration, and ensure compliance with data governance standards.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

Lead design and delivery of the enterprise Data Platform including data lake, analytics, and certified data products. Architect solutions, automate pipelines, implement monitoring, mentor engineers, translate business needs into technical architectures, and document systems for sustainability.

The AI-Native Data Platform Engineer will design data foundations for AI systems in wealth management, architecting data pipelines, models, and frameworks to enable autonomous financial agents.

Design, build, and maintain scalable ETL/ELT data pipelines and analytical platforms on AWS and Databricks. Migrate legacy workflows to cloud-native services, implement data lake and catalog solutions, enable AI/RAG/vector search, ensure FedRAMP/NIST compliance, optimize performance, and mentor junior engineers while collaborating in Agile teams.

The Senior Data Engineer will design and operate the data platform, build ELT/ETL pipelines, optimize data performance, and ensure data quality while collaborating with business teams.

The Senior Data Engineer designs scalable data solutions to harmonize data across various ERP systems, implementing ETL/ELT pipelines and ensuring data quality and governance.

Design, develop, and execute enterprise CRM data migrations into Microsoft Dynamics CRM/365 using KingswaySoft and SSIS. Extract, transform, cleanse, validate, and load structured and unstructured data from legacy systems, optimize SQL/SSIS, troubleshoot performance, support integrations and customizations, perform validation testing and production cutovers, and document migration architecture and procedures while ensuring data governance and security compliance.

As a Staff Data Engineer on the Data Lake team, you will architect, build, and scale distributed ETL pipelines, ensuring data quality and leading the engineering team. You will also drive large-scale data processing and technical initiative leadership.

The Sr. Data Engineer will develop KPIs for infrastructure costs, analyze data, create reports, and enhance data systems for Starlink's ground network.

The role involves designing and optimizing data pipelines in ClickHouse, ensuring reliability, monitoring performance, and coaching teams on best practices across data operations.

The Senior Data Engineer will design and maintain data pipelines and infrastructure for fraud detection analytics, ensuring data integrity and supporting testing across platforms.

Lead design and implementation of batch and streaming data pipelines, build data models, implement data quality and testing, manage orchestration and IaC, mentor engineers, and communicate technical direction and tradeoffs to stakeholders.

Design, build, and optimize scalable data pipelines and models using Snowflake, SQL, Python, Kafka, dbt, and Argo. Support near-real-time integrations, CI/CD workflows, data quality, and performance; mentor engineers; partner with product and analysts to deliver production-ready, AI-enabled data solutions.

The Sr. Data Engineer will build and manage data pipelines for large datasets, collaborate with teams, and leverage cloud technologies for data processing.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Design, build, and maintain scalable data pipelines, ETL/ELT processes, data lake and warehouse infrastructure, and cloud-based data platforms. Optimize systems for performance, reliability, security, and cost while implementing monitoring, governance, and data quality practices. Collaborate cross-functionally with data scientists, analysts, engineering, and product teams to deliver reliable data solutions and improve the data ecosystem roadmap.

Designs and maintains ETL pipelines, data architectures, databases, data models, and master data management solutions. Analyzes, profiles, cleans, and validates complex datasets; establishes data quality standards; and develops automated data management processes. Partners with architects, data stewards, and business stakeholders to improve data integrity and support business requirements. Communicates insights through reports and presentations while using cloud, database, streaming, CI/CD, and data modeling technologies.

Designs and delivers a global analytics platform supporting reporting, visualizations, self-service analytics, and embedded data products. Responsibilities include data collection and processing, semantic modeling, warehouse and pipeline development, query optimization, governance, analytics enablement, and stakeholder collaboration. The role provides actionable insights from complex travel data and builds integrated analytics applications using cloud platforms and business intelligence tools.