Top Senior Data Engineer Jobs

Lead design and engineering of an enterprise graph database platform for fraud and claims. Build graph data models, large-scale pipelines, optimize hybrid/cloud platforms, improve data governance, and consult cross-functionally to resolve high-risk data engineering challenges.

The Geospatial Data Engineer designs and implements data architectures and systems for intelligence analysis, supporting GEOINT analysts with automation and model creation.

Design, build, and maintain scalable cloud-native data pipelines and ETL/ELT solutions using Python/PySpark, Databricks, DBT and AWS/Azure services. Collaborate with architects, data scientists, and product teams to optimize data models, ensure data quality, monitor pipeline performance, and drive architectural improvements and automation.

Design and deliver enterprise-scale data models and analytics-ready datasets in Snowflake; build reliable ELT/ETL pipelines (batch and near-real-time); implement data quality, observability, and performance optimizations; publish curated data to downstream systems; enforce documentation, lineage, schema evolution, and secure handling of sensitive data while collaborating with product, operations, and engineering teams.

The Data Engineer will architect and deploy Big Data environments, manage data pipelines, and ensure data integrity across the organization.

Design, build, and maintain scalable data pipelines and cloud data infrastructure. Ensure data quality, governance, and RBAC. Orchestrate batch ML pipelines, optimize performance and costs, collaborate with stakeholders, mentor team members, participate in on-call and incident management, and evaluate vendor/architecture tradeoffs.

Founding data engineer for an AI-focused incubator building 0->1 solutions: design and operate scalable ETL/ELT pipelines, ensure observability, work with BigQuery/Airflow/dbt/AWS Glue and varied databases, and contribute using Python and JS/TS in a seed-stage startup environment.

You will design and optimize cloud-based data pipelines in AWS, develop automation frameworks, and enhance data architecture for financial reporting and actuarial modeling.

Lead and mentor data engineering team members while designing, building, and optimizing scalable data pipelines and architectures; extend ML platform tooling; enable analytics and data science workflows via ETL, SQL, Python and AWS services.

Design and maintain scalable data pipelines, collaborate with cross-functional teams, manage data architectures, optimize Snowflake performance, and enhance data workflows.

As a Staff Data Engineer, you'll architect and model data, create ETL pipelines, and standardize datasets for compliance teams. You'll guide best practices and lead data solutions while collaborating with various stakeholders.

Lead design, implementation, automation, and maintenance of large-scale ETL pipelines; optimize SQL and database performance; translate business needs into data requirements; enforce best practices (version control, code reviews, validation); mentor junior engineers; deliver timely, robust data solutions for global clients.

The Data Engineer will design and build scalable data systems, support AI/ML integration, and collaborate across teams for the development of Canoe's Alts Data Platform.

Build and own end-to-end sales data pipelines and curated marts in Snowflake/dbt; implement monitoring, tests, and governance; run reverse-ETL to operational systems; partner with Sales, Ops, Finance, and People to deliver production-ready analytics products.

Lead design, build, and maintain scalable data pipelines and warehouses. Drive technical roadmap, mentor engineers, implement data quality/testing/monitoring, optimize performance and cost, and collaborate cross-functionally to ensure reliable data for BI, ML, and applications.

Lead design and build of a scalable, secure cross-cloud data platform and marts. Drive selection and optimization of the modern data stack, enforce governance and lineage, and establish reusable data models and best practices to support analytics, BI, and ML use cases across product and engineering teams.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.

Lead engineering and automation for a data collaboration ecosystem: design secure, scalable Snowflake/Databricks clean room architectures, build ELT pipelines (Snowpark/PySpark), implement MLOps and AI/LLM integrations, enforce RBAC and privacy controls, drive observability, cost optimization, onboarding, and operational excellence for partner-facing data products.

We're seeking a Data Engineer with 5+ years of experience to build data processing solutions using Python, design data models, and process large data streams while ensuring high performance across various data technologies.

Lead and deliver large-scale data processing and integration initiatives. Build and maintain optimized, highly available ETL pipelines, data models, and data warehouses. Resolve technical issues, ensure compliance, and collaborate with teams to meet strategic data engineering goals.

As a Data Engineer, you will build and maintain scalable data pipelines, implement data engineering frameworks, and support AI initiatives. You will also design processes for data cleansing, transformation, and orchestration while adhering to engineering standards.

Designs and implements scalable multi-tenant data solutions and pipelines using Python, SQL, Snowflake, Snaplogic, Azure and AWS. Leads architecture design, ensures QA readiness, documents systems, mentors engineers, and coordinates cross-team project delivery on-time and on-budget.

Design, develop, and monitor large-scale cloud-native data solutions and ETL pipelines; support ML model deployment, ensure code hygiene and CI/CD, mentor engineers, produce documentation and runbooks, and engage with clients to deliver analytics-driven solutions.

The Data Engineer role involves building pipelines, implementing frameworks, and exploring AI for data management. Requires communication of complex concepts and adherence to engineering standards.