Staff Database Engineer

NetDocuments

11h•Hybrid

About The Position

NetDocuments is seeking a Staff Database Engineer to provide enterprise-level technical leadership across our global data platform. In this highly impactful role, you will define technical strategy, architect complex multi-cloud systems, and drive multi-quarter initiatives that shape the reliability, scalability, and cost efficiency of data systems serving a global customer base. As a Staff Database Engineer focused on data, you will operate at the intersection of architecture, execution, and mentorship. You’ll remain deeply hands-on while setting standards, tackling ambiguous problems, and serving as a technical authority for data platform decisions. You’ll partner directly with leadership to translate business needs into durable technical roadmaps and guide the evolution of our data infrastructure across AWS and Azure.

Requirements

7–10+ years of experience as a Data Engineer, Database Engineer, Platform Engineer, or similar role.
Proven track record designing and owning large-scale, production data systems (TB+ scale).
Deep expertise in Python and SQL for data operations and workflow orchestration.
Expert-level experience with AWS services including Glue, Lambda, Step Functions, ECS, EC2, DynamoDB, and DocumentDB.
Production experience with Azure data services such as Data Factory, Synapse, and Functions.
Strong database expertise across relational, NoSQL, and analytical systems (Snowflake, PostgreSQL, DynamoDB, DocumentDB).
Demonstrated experience leading major data migrations across clouds, regions, or legacy systems.
Deep understanding of distributed systems concepts including replication, consistency, and partitioning.
Advanced observability and monitoring experience using tools such as CloudWatch, Datadog, or Azure Monitor.
Strong incident response experience, including leading production outages through resolution and post-mortem.
Proven ability to drive technical initiatives across multiple teams through influence rather than authority.
Excellent communication skills with the ability to explain complex technical concepts to engineers and executives alike.

Nice To Haves

Experience with Couchbase or similar distributed document databases.
Experience operating large-scale, multi-tenant systems serving hundreds of customers.
Background in document management, content platforms, or hierarchical storage systems.
Experience with Infrastructure as Code (Terraform, CloudFormation, Bicep).
CI/CD expertise for data engineering workflows.
Experience with DBT, Coalesce, or similar data transformation frameworks.
Familiarity with AI/LLM integration patterns, RAG architectures, or vector databases.
Proven cloud cost optimization impact with measurable results.
Technical writing, conference speaking, or open-source contributions.

Responsibilities

Own the technical roadmap for data infrastructure across AWS and Azure multi-cloud environments.
Drive architectural decisions for multi-region, cross-account data platforms supporting global operations.
Establish engineering standards and best practices for data pipelines, database design, reliability, and observability.
Lead incident post-mortems and drive systemic improvements that prevent entire classes of failures.
Influence product and engineering roadmaps by identifying technical risks, constraints, and opportunities.
Define capacity planning and cost optimization strategies to ensure performance, reliability, and financial efficiency at scale.
Architect greenfield systems for large-scale data migrations (e.g., Couchbase to DocumentDB or DynamoDB at TB+ scale).
Design fault-tolerant, self-healing data pipelines using AWS Glue, Step Functions, Lambda, ECS, and Azure Data Factory.
Define data modeling strategies across Snowflake, PostgreSQL, DynamoDB, and DocumentDB in multi-region environments.
Design observability into all systems, including monitoring, alerting, tracing, and debugging capabilities.
Own backup and disaster recovery strategies, including RTO/RPO planning, PITR, and cross-region replication.
Drive indexing, query optimization, and performance tuning for databases handling billions of documents.
Architect security patterns covering IAM, secrets management, encryption at rest and in transit, and access controls.
Partner with the Director of Data Engineering on strategic planning, prioritization, and roadmap execution.
Collaborate with senior leaders across Engineering, Product, and Analytics on enterprise technical strategy.
Work across organizational boundaries to deliver initiatives requiring coordination across multiple teams and time zones.
Translate business requirements into technical designs and clearly communicate trade-offs to non-technical stakeholders.
Represent the data organization in architecture reviews and cross-functional technical planning forums.
Lead by example through hands-on development of critical systems, migrations, and infrastructure.
Own and resolve complex production incidents affecting large-scale, distributed systems.
Drive cloud-to-cloud, legacy-to-modern, and cross-region data migrations.
Implement streaming and CDC solutions using Kafka, Kinesis, AWS DMS, and related technologies.
Build automated data quality, validation, and testing frameworks.
Optimize performance, reliability, and cost across critical workloads.
Automate operational workflows using Python, Infrastructure as Code, and cloud-native tooling.
Mentor Senior and Data Engineers through code reviews, design reviews, and technical guidance.
Raise the technical bar through documentation, standards, pairing, and knowledge sharing.
Help engineers grow from mid-level to senior and senior to staff through intentional coaching.
Promote a culture of operational excellence, including incident response, runbooks, and blameless post-mortems.