Top Senior Data Engineer Jobs

Lead and architect large-scale data products and pipelines across teams. Design and deliver ELT/ETL solutions, evaluate tools, ensure scalability and integrity, influence technology decisions, and research emerging big-data/cloud methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake). Partner with architects and stakeholders to drive implementation and operationalize production workloads.

Design, build, and maintain large-scale data pipelines and APIs for Ventura OS. Optimize data processing workflows, integrate ML models into production, ensure data quality and observability, and collaborate across teams to drive architecture and data infrastructure decisions for streaming and content recommendation use cases.

Design, build, and operate Azure Lakehouse architectures (Databricks, ADLS Gen2, Synapse, ADF); develop and optimize scalable ETL/ELT pipelines and Spark batch/streaming jobs using Python, SQL, and Scala; ensure data quality, performance tuning, cost optimization, production deployments, monitoring, and cross-functional collaboration.

Design, implement, and maintain data analytics platforms, pipelines, dashboards, and ML models for animal nutrition research. Collaborate with researchers, barn managers, and cross-functional teams to collect and analyze farm data, deliver insights and alerts, and develop digital products to improve research, productivity, and sales.

Lead the architecture and implementation of a new People Analytics platform on a modern data stack, ensuring AI readiness, governance, and security while optimizing for performance.

As a Senior Data Engineer, you will build complex data solutions and pipelines, support analytics growth, and educate users. Collaboration and advanced technical skills are essential.

Design, build, and operationalize scalable data pipelines and transformations on cloud platforms. Ensure data governance, quality, and security; collaborate with data science to support ML model operationalization; mentor engineers and drive architectural decisions for enterprise analytics.

Design, build, and operate production data pipelines across AWS, Databricks, and Snowflake. Modernize and migrate legacy AbInitio workloads, embed data quality/observability/lineage, optimize cost/performance, drive CI/CD and DataOps practices, integrate AI coding tools, mentor engineers, and standardize reusable pipeline frameworks.

Design, build, and maintain cloud-based data infrastructure and ETL/ELT pipelines (Azure, Databricks, Snowflake, Fabric). Lead cloud migrations from on-prem SQL Server, implement Medallion/Lakehouse architectures, ensure data quality and performance tuning, collaborate with analysts and data scientists, and mentor junior staff.

Design, build, and maintain scalable ETL/data pipelines across distributed systems. Ensure data quality, integrity, security, and high availability. Monitor and optimize pipeline performance, perform root cause analysis, document systems, collaborate with global teams, and participate in on-call rotations to support production data systems.

As a Senior Data Engineer, you will develop data pipelines, architect innovative data products, and integrate AI/ML models to enhance business insights.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

The Data Engineer will optimize data infrastructure, modernize SQL processes, support data governance, and mentor team members while enhancing analytics capabilities.

Design and implement scalable data infrastructure and pipelines on AWS using Spark and Scala. Build fault-tolerant batch and streaming workflows, optimize storage formats and engines, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable data assets and APIs.

The Data Engineer will architect and maintain modern data platforms, manage ETL/ELT pipelines, integrate diverse data sources, and champion data governance while supporting advanced analytics and AI workloads.

The Senior Data Engineer designs, builds, and maintains data pipelines and ensures data quality controls while supporting data analytics and reporting needs.

Design, build, and own data infrastructure and ETL/ELT pipelines (Airflow, S3, Lambda) into a governed Snowflake warehouse. Implement data quality, IaC (Terraform/CDK), CI/CD, and analytics solutions (SQL, Tableau). Enable ML/LLM use cases like forecasting and anomaly detection and deliver automated reporting and data-driven marketing outputs.

The Senior Data Engineer will design, develop, and maintain data platforms, create ETL processes, handle data quality issues, and mentor teammates while ensuring scalability and performance in data solutions.

Design and implement scalable AWS-based data infrastructure using Spark and Scala. Build fault-tolerant batch and streaming pipelines, optimize storage formats and engines, collaborate with Data Science and Product, implement automated data quality checks, and deliver performant data assets and APIs.

Build and maintain scalable ETL pipelines using Python, Spark, and Airflow; collaborate with AI/ML and Product teams to deliver AI-native data products; identify and resolve ETL bottlenecks; ensure code quality through reviews and tests; own sprint deliverables and contribute to roadmap planning and major epics.

Lead architecture and implementation of an AWS-native data platform powering analytics, ML, and AI workflows. Build scalable ETL/ELT pipelines (Airflow, Fivetran, dbt), enforce governance, observability (Datadog), and data quality, and provide technical leadership across Data Science, Analytics, Product, and Engineering.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

Design and build scalable, fault-tolerant batch and streaming data pipelines and data models for Roku devices and clients. Maintain petabyte-scale data warehouse, ensure data quality, optimize performance, debug large clusters, and collaborate across teams to deliver trusted analytics products and influence roadmap.

Design and build scalable batch and streaming data pipelines and data models for Roku devices and clients. Own data mapping, transformations, quality standards, debugging, and performance tuning on petabyte-scale warehouses. Influence architecture and product roadmap, support existing platforms, and deliver trusted data products enabling analytics and product decisions.

Lead architecture and implementation of fleet telemetry, time-series storage, streaming pipelines, and CRM/warehouse integrations on AWS. Build tools for proactive fleet health, partner cross-functionally (firmware, manufacturing, ops), support on-call as systems mature, and design LLM-driven automations to increase team leverage.