Top Senior Data Engineer Jobs

In this role, the Senior Data Engineer designs and implements data architecture for analytics and ML initiatives, develops ETL/ELT pipelines, and ensures data quality and compliance, while mentoring junior team members.

The Sr. ETL Informatica Systems Engineer develops ETL applications for the EDW/BI program using Informatica tools, managing complex SQL and APIs.

Lead design, build, and maintain complex ETL/ELT data pipelines and integration solutions to support analytics and reporting. Ensure data quality, optimize processing for performance and scalability, monitor pipelines, document data lineage and procedures, and collaborate with stakeholders and analysts to resolve data issues and requirements.

Design, build, and maintain scalable Databricks (PySpark/SQL/Delta Lake) pipelines to transform SAP S/4HANA and ECC data into curated, governed data products. Implement data quality, lineage, observability, and access controls (Unity Catalog, Immuta), collaborate with SAP experts and analytics teams, and mentor engineers to deliver production‑grade datasets for analytics and AI/ML.

This role involves leading data strategy and managing a team to build and maintain multimodal datasets, ensuring data quality and pipeline efficiency.

Lead technical design and hands-on development of Pantheon’s data platform, extending ingestion, curation, retention services and ML/LLM infrastructure. Mentor engineers, drive architecture and engineering standards, operate in a DevOps model, partner cross-functionally, and participate in on-call support to ensure reliable, compliant data access and analytics.

Design, build, and optimize end-to-end data pipelines and ETL/ELT processes, enforce data governance and lineage, create enterprise datasets and data models, mentor team members, and implement CI/CD for data deployments to support analytics and advanced analytics use cases.

Design and build SOCOTEC's enterprise data platform: scalable Databricks/Spark/Delta Lake pipelines, data models, and MDM. Ingest from ERP/CRM, enable batch and near-real-time processing, ensure data governance, quality, lineage, and provide datasets for analytics and AI while driving architecture and observability.

Design, build, and maintain production-grade data pipelines, Python services, and Databricks workloads for a large-scale financial data platform. Improve performance, reliability, observability, and data models; troubleshoot issues; participate in architecture, code review, and cross-team collaboration to deliver enterprise reporting and integrations.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

Build and scale Allocate's AWS-based data lakehouse and pipelines (batch and real-time). Model financial entities and integrate internal/third-party sources. Enable ML/AI workflows, vector and knowledge-graph integrations, CI/CD and containerized deployments, and collaborate with engineering to deliver reliable, production-grade data and AI infrastructure.

Lead architecture and implementation of enterprise-scale, production data pipelines and ecosystems for global, customer-facing products. Collaborate with product and engineering leadership, mentor peers, enforce code and CI/CD standards, and optimize data storage and performance for high-availability, defense-focused monitoring solutions.

Own and harden Plot's core data platform: stabilize high-throughput ingestion, design read-optimized schemas and partitioning, separate transactional vs analytical workloads, ensure performant data access for dashboards and AI agents, write RFCs, and raise reliability and observability across teams.

Design and own end-to-end data domains and pipelines for plant sensors, lab results, and historians. Build schemas, ensure data quality, observability, and lineage, and supply model-ready time-series and analytical datasets to ML and operations teams. Mentor junior engineers and define data contracts.

Design, build, and maintain scalable data models, ETL/streaming pipelines, and cloud-native data platforms. Ensure data quality, governance, performance tuning, and enable ML workflows. Lead cross-functional teams, mentor engineers, and implement CI/CD, monitoring, and cost-optimized solutions to support analytics and real-time inference.

The Senior Data Engineer will design and manage data pipelines for massive datasets, ensuring quality, cost management, and effective data operations. Responsibilities include overseeing data flows, monitoring data quality, and managing vendor partnerships.

Design, build and maintain a self-service data platform to enable teams to create data products. Support real-time analytics, batch processing and ML workloads. Implement secure, scalable, compliant infrastructure with IaC and automation. Enable ingestion, processing and consumption of data at scale. Mentor teammates and drive engineering excellence.

The Principal Database Architect & Engineer will own the data components of complex infrastructure solutions and lead teams to deliver innovative database technology solutions, ensuring optimal performance and operational efficiency.

The role involves building scalable ELT/ETL pipelines on GCP, utilizing SQL and Python, and managing security and infrastructure automation while ensuring real-time processing and resource provisioning.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

Lead architecture, implementation, and optimization of scalable data platforms, ETL/ELT pipelines, and data governance. Ensure security and compliance, mentor junior engineers, drive CI/CD and IaC for data workflows, and collaborate with stakeholders to deliver actionable analytics and reporting.

Design, build, and maintain scalable distributed data pipelines and a secure data lakehouse for streaming and batch processing to support real-time analytics, ML, and experimentation. Automate, test, and harden workflows, architect logical and physical data models, build ML model features, and collaborate with product, analytics, and data science teams to turn data into value.

Build and operate ingestion and transformation pipelines, model and test core warehouse data, enable analytics and reporting, and maintain ML data infrastructure feeding matching and recommendation models. Partner with Engineering, Product, and Data Science to ensure reliable, documented, and trusted data at scale.

Lead hands-on design, development, review, and optimization of production data pipelines and platform capabilities. Provide technical leadership, mentor engineers, drive CI/CD, observability, automation, and scalable data platform architecture to support analytics and ML workloads within an Agile environment.

Technical lead for data engineering who designs, builds, and owns scalable Snowflake ELT pipelines and data models. Mentors engineers, drives standards, optimizes performance and costs, and partners with product, analytics, QA, and governance to deliver observable, high-quality data solutions. Contributes to platform strategy, DataOps/CI/CD adoption, and ensures data quality, testing, and documentation.