Staff Data Platform Engineer

Murmuration builds technology, data-driven insights, and tools that help partner organizations strengthen civic engagement and organize effectively in their communities. The Staff Data Platform Engineer will improve how engineering teams provision, secure, monitor, troubleshoot, and operate production data systems by building reusable infrastructure, establishing data platform standards, optimizing databases, and providing technical leadership across teams.

Responsibilities:

• Create re-usable IAC (infrastructure as code) to manage database resources
• Secure the databases including provisioning human and system users via automation
• Ensure operational monitoring is integrated with application and end-to-end data flow monitoring; and
• Optimize database runtimes
• Designing, implementing, and testing logical and physical database backup and recovery schemes in accordance with Disaster Recovery and Business Continuity objectives
• Review what data store is best suited for an application
• Evaluate our database ecosystem and help refine the Data North Star
• Evaluate tools and services and ensure our data tool belt is well balanced with power, extensibility, training, and operational effort
• Help teams model their data schemas
• Review data access libraries and general access patterns
• Build paved roads for database infrastructure in the cloud: IAC is plug and play with minimal effort and has best practices built in; and
• Improve and expand existing code bases: reinforce secure coding practices, identify vulnerabilities early, and treat data privacy and access control as first-class concerns
• Reduce technical debt, improve system quality, and contribute to objectives that span the broader organization
• Establish best practices for data schemas, data sharing, data access layers; raise the technical bar across the organization through documentation, reference implementations, advocacy, and role modeling
• Mentor senior engineers and help emerging technical leads build the judgment, ownership, and skills to grow; lead technical discussions, drive design consensus, and model the standards you expect from others
• Champion secure data practices at a systemic level, identify vulnerabilities across the product, and treat data privacy and access control as organization-wide concerns; and
• Be like Ted Lasso: believe, build trust, and demonstrate kindness, empathy, optimism, curiosity, and vulnerability

Requirements:

• Deep, hands-on expertise across critical technical domains with the proven ability to lead system design, architectural patterns, and engineering best practices; your sound technical judgment shapes important decisions
• Ability to choose the best tool for a scenario by optimizing the most functional coverage for the least total cost of ownership
• Ability to reason across No-SQL vs. relational stores, transactional vs. analytic data architectures, and make sound design decisions for the systems that depend on them
• Comfort making sound decisions with imperfect information; able to design long-term architectures with scale, reliability, security, and maintainability as first-class concerns, and to clearly articulate tradeoffs and alternatives explored
• Ability to communicate and defend well-reasoned solutions through written documentation, sharing context, what alternatives were considered, and how conclusions were reached
• A proactive steward of technical quality, identifying and prioritizing technical debt, defining test strategy, and evaluating risk from bugs and architectural problems before they become blockers; and
• Skill at debugging the most complex problems at any level of the stack
• Proven ability to lead technical strategy and execution for significant initiatives spanning multiple teams or systems, balancing quality, performance, and cost while keeping stakeholders aligned on tradeoffs and risks
• Proven experience in designing objectives aligned with division and organizational goals, anticipating technical challenges and proposing solutions before they become blockers
• Demonstrated experience in the estimation of large, cross-team projects with significant unknowns, including mitigation plans for resolving those unknowns to reduce risk and deliver incremental value
• Proven strategies to involve the right people, delegate clearly, communicate consistently, and follow through as an owner until an objective is delivered; and
• Ability to multiply team and engineering effectiveness through technical leadership, tooling, infrastructure, and process improvements
• Technical leadership across multiple teams, acting without direct management responsibilities, influencing outcomes through role modeling, documentation, and advocacy rather than authority
• Demonstrated track record as a mentor to senior engineers with a proven ability to develop future technical leaders, building their judgment, ownership, and skills through 1:1 guidance and small-group knowledge sharing
• A driver of standards and best practices that raise the technical bar across the organization, creating processes that instill ownership behavior in others
• Ability to represent engineering effectively in cross-functional discussions, leading alignment across technical and non-technical stakeholders on complex, multi-team initiatives; and
• A leader by example, proactively sharing context and learnings, building POCs or prototypes where most cost-effective, and creating the kind of high-trust, high-performing team culture that makes everyone better
• 10+ years of professional software engineering experience with demonstrated data specialization and a track record of delivering in production across a variety of transactional and analytic scenarios
• Experience driving secure coding practices, data privacy principles, and access control patterns as applied in production systems
• A test-driven mindset with experience writing, maintaining, and driving test strategy at the team or product level
• A track record of effective collaboration with product, data science, and R&D teams, bridging technical and domain-specific perspectives across disciplines; and
• Experience with using AI as a daily assistant, along withthe judgement needed to know when and where to best use or not use AI
• Expert level experience with No-SQL, relational, and columnar data stores: either direct or transferable operating experience with Mongo, DynamoDb, PostgreSQL, and Snowflake
• Expert level ability to write fluent SQL and No-SQL, design schemas, and define migrations and optimize read and write performance
• Deep data design skills including No-SQL collections and indexing, relational normalization, and data warehousing facts and dimensions
• Experience working with transformation tools such as dbt
• Experience with data replication and change data capture (CDC) tools such as Kafka source connectors, Database Migration Services (DMS), or AirByte
• Experience with data pipeline orchestration tools such as Dagster or Airflow with an understanding of scheduling, dependency management, and pipeline reliability
• Experience with streaming data pipelines such as Flink
• Working knowledge of time series data modeling and its applications; and
• Working knowledge of geospatial data modeling and usage
• Deep experience with cloud-native architectures, distributed systems, and production-grade software at scale; production experience with AWS, including services for compute, storage, and observability
• Proficiency with IAC tooling such as CDK, SAM, Serverless Framework, or Terraform
• Working knowledge of deployment pipelines such as Git Hub Actions or Bit Bucket Pipelines; and
• Direct experience with observability tooling: logging, metrics, and tracing using tools such as CloudWatch, Datadog, New Relic, Prometheus, or Grafana
• Familiarity with Voter File Data
• Experience with or interest in political data; and
• Background in political tech, civic tech, advocacy, or mission-driven organizations