Top Senior Data Engineer Jobs

Lead the development and optimization of data transformation processes using dbt Core, Snowflake, and Python. Mentor engineers and ensure deliverables meet analytics needs.

The Senior/Staff Data Engineer will design and scale the core data platform for healthcare systems, focusing on infrastructure, tooling, and governance while mentoring engineers and collaborating with various teams.

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.

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, 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.

Build, operate, and modernize scalable data pipelines and warehouse environments for lottery reporting, analytics, and AI readiness. Improve ingestion, transformations, data models, contracts, observability, lineage, and onboarding patterns. Automate operations, troubleshoot production issues, mentor engineers, and support migration from legacy to cloud architectures while ensuring data quality, reliability, and regulatory continuity.

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.

As a Senior Data Engineer at Auger, you will build data systems to transform customer data into a unified ontology for analytics and AI workflows, ensuring data quality and managing the data lifecycle.

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.

Design, build, and maintain enterprise data engineering solutions and ETL/ELT pipelines using ADF, SSIS, and SAP Data Services. Develop and optimize database schemas and complex SQL in Oracle and SQL Server, implement data warehouse/data lake architectures (star/snowflake), ensure data quality and governance, create Power BI reports, automate workflows with Python and Shell, troubleshoot pipeline failures, support SDLC, and mentor junior engineers.

Lead architecture and scaling of the Databricks data warehouse and self-service data platform. Build reusable batch and streaming frameworks, enforce governance, SLOs, lineage, observability, CI/CD, and multi-tenancy. Mentor engineers, run design reviews, and ship documented patterns to enable analytics, data science, and app teams to move quickly without blocking on platform tickets.

The Senior Data Engineer designs and develops scalable data architectures across platforms, mentors team members, and enhances data engineering capabilities for insights and decision-making.

Lead architecture and modernization of the enterprise data platform. Build scalable serverless data pipelines with Airflow, dbt, Python, and AWS. Integrate Fivetran, Redshift, and Sigma, implement observability, enforce data governance, and mentor engineers to improve reliability and analytics deliverables.

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 design, build, and maintain scalable batch and streaming data pipelines and data warehouse models. Ensure data quality, observability, performance, and security. Own workstreams, support production incidents, and enable analysts and downstream applications.

Design, build, and optimize cloud data platforms using Azure, Databricks, and Fabric. Lead discovery, architecture, and data ingestion (batch/streaming), implement medallion/lakehouse designs, engineering transformations, and recommend governance, DevOps, and security best practices while working directly with clients.

Administer, stabilize, and scale Oura's global Databricks environment. Manage workspace governance, cluster policies, access control, cost monitoring, job scheduling, and incident SLAs. Onboard teams, resolve performance and reliability issues, and partner with IT and Data Architecture. Over time contribute to pipeline development, Spark optimization, CI/CD, and infrastructure-as-code to support domain-oriented data mesh initiatives.

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.

As a Data Analytics Engineer, you will build data pipelines, develop KPIs, collaborate with stakeholders, and promote data-driven decision-making.

The Senior Data Engineer will design and manage petabyte-scale data pipelines, ensuring data quality and architecture for operational decision-making and ML training.

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 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.

The Senior Data Engineer will optimize data architecture, troubleshoot integrations, and refactor legacy systems within a product team focused on client applications.

Own and improve the company data stack: expand the data warehouse, build and streamline Python-based ingestion and ETL processes, refactor dbt models, maintain data quality, standardize reporting, and collaborate with engineering and analysts. Act as technical owner for parts of the stack and proactively drive improvements and automation.