Top Senior Data Engineer Jobs

Lead design and implementation of Databricks/Azure data solutions to ingest, store, transform, and distribute large-scale retail data. Own features through the SDLC, mentor engineers, lead cross-functional collaboration, build REST APIs on Kubernetes, execute testing, and set technical strategy with Product, Data Science, and Architecture.

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 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.

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.

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

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.

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.

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.

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

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.

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 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.

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.

Design, build, and scale streaming and batch data pipelines and embedding workflows; integrate vector stores and AI platform services; implement observability, data quality, and governance; mentor engineers and lead production-ready AI data foundations supporting ad technology.

Design, build, and maintain Databricks and cloud-based data ingestion, storage, and distribution solutions. Implement ETL/warehousing, pipeline orchestration, CI/CD, automated testing, and mentor junior engineers while collaborating across architecture and scrum teams to deliver scalable data products.

Design, build, and lead a scalable, configuration-driven data integration platform. Improve performance, automate monitoring and deployments, provide escalated support, and collaborate across product and engineering to deliver reliable, secure data integrations.

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.

The Staff Data Engineer will build and optimize data pipelines, ensure data reliability, collaborate with teams, and shape the data engineering landscape at CookUnity.

Design, build, and operate petabyte-scale data infrastructure: real-time ingestion, storage (open table formats), and serving. Architect scalable Iceberg-based data lakes, optimize Spark pipelines and streaming (Kafka/Flink), drive reliability, cost efficiency, and data contracts; collaborate with product and platform teams and establish best practices and tooling.

The Senior Data Engineer will manage data tuning on relational databases, utilize Big Data technologies, and coordinate with technical teams and business users.

Lead design and implementation of the enterprise data platform: architect scalable warehouse/lakehouse solutions, build and optimize ETL/ELT pipelines, enforce data quality and governance, tune analytical workloads, and enable reporting and self-service analytics in support of BI and AI initiatives.

Design, build, and operate large-scale AWS-based ETL pipelines using Glue/PySpark to ingest, transform, and curate multi-format data into Apache Iceberg tables. Ensure data quality, metadata management, semantic layer creation (Trino/Athena), CloudFormation deployments, documentation, and compliance within a FedRAMP federal agile environment.

Lead the analytics data layer: design and operate a ClickHouse-backed warehouse, define and validate trusted metrics, build customer-facing React dashboards and internal Grafana/self-serve tooling, and ensure data quality, lineage, and documentation for telemetry-derived insights.

Design, build, and maintain data ingestion, ETL, storage, and analytics systems to measure and scale Starlink network performance (including Wi‑Fi). Automate metric aggregation, detect widespread application issues, lead investigations, fuse multi-source data, and apply analytics and ML models to vehicle- and ground-generated data.

Design, build, and iterate data engineering pipelines, dashboards, and reports to support analytics and data science. Partner with stakeholders to translate requirements into engineering solutions, promote self‑service analytics, define best practices, and support implementation using Databricks, Snowflake, and Azure components.