At Murmuration, we believe that America’s promise is shaped and reshaped by the best ideas and ideals of its communities, and the dreams of the people who believe in a better life for themselves, their families, and each other.  We help organizations build power in their communities in four key ways: we organize a network of values-aligned partners; we provide deep, data-driven insights into people, places, and perspectives; we develop tools that make organizing and engagement easy and more effective; and we offer services that strengthen our partners’ capacity to lead change in their communities. We envision an America where every community has what it needs to help people lead healthy, free, and dignified lives. We work to redesign the systems and structures we all depend on — how we learn, live, govern, and solve problems — so that they are just, equitable, resilient, and rooted in shared responsibility. By strengthening the ties that hold communities together, we aim for civic life defined by collective action and care, with effective leadership that truly represents everyone.  We are a collaborative, curious, and creative team of organizers, scientists, teachers, technologists, campaign veterans, and more who share the unwavering belief that we can use our gifts in service of transforming America — together. We’ve built our team guided by the belief that the whole is greater than the sum of its parts. And so we support each other relentlessly — rallying together to face challenges the same way we celebrate each other’s wins. About the Position You're a mission-driven data engineer with a track record of building infrastructure that delivers real impact. You're deeply curious not just about how systems work but about the messy, real-world data they must support. You've done this before: you understand what "good" looks like, you deliver high quality solutions, and you help the teams around you operate more effectively. At Murmuration, you'll work with voter files from 50 states (each with its own format and quirks), census data, polling results, geographic boundaries, election returns, and more. These data sources arrive at different cadences, anywhere from multiple times a day during early voting to once a year from the census. Your role is to bring order to this complexity by building the pipelines, data contracts, and governance that transform these disparate inputs into Atlas, our unified representation of American civic life. This role is for someone who's energized by complex data problems, comfortable with ambiguity, and motivated by the understanding that strong infrastructure and data foundations is a core part of what makes research, product development, and meaningful civic impact possible. You'll partner closely with data scientists, researchers, and product teams who rely on what you build. You also stay curious about emergent technologies, particularly AI, and apply them thoughtfully to amplify your impact and the effectiveness of the broader team. Job Level P4 What You'll Do - Own data pipelines and infrastructure: Design, implement, and evolve scalable, production-grade systems using tools such as Dagster, Airflow, Snowflake, AWS, MongoDB, and dbt. Apply a cloud-native and DevOps mindset using CI/CD, infrastructure-as-code, monitoring, and automated testing to build reliable systems. Partner with cross-functional teams to deliver solutions that meet both immediate product needs and long-term organizational strategy. - Lead data ingestion and integration: Bring in complex, high-volume datasets while ensuring strong data contracts, freshness, quality, integrity, and lineage, and build systems that empower domain experts to contribute to and maintain their own data pipelines. - Transform raw data into trusted data products: Convert raw inputs into structured, usable datasets  that empower our analytical and product teams. Collaborate closely with operational data managers to ensure data models and intuitive, reliable alignment with how data is consumed in practice. - Leverage AI: Make informed judgement calls about how AI can be a force-multiplier for both your own work and the team’s and how it can’t. - Elevate the team: Mentor engineers, actively shape technical direction through architectural reviews and roadmap planning, and build team culture through documentation and knowledge sharing.

• Lead and develop robust data pipelines using Databricks, Azure Data Factory, Python and PySpark to support large-scale data projects. • Design and implement scalable solutions for integrating and processing data from multiple sources, including transactional and operational data, ensuring high data quality and governance. • Work with SQL and Databricks to extract, transform and prepare data, as well as create complex transformations to meet analytical and operational needs. • Collaborate with business and data teams, helping translate technical requirements into effective solutions that directly impact logistics operations. • Develop and automate data ingestion, transformation and analysis processes using tools such as Azure Data Factory, APIs, Kafka and Oracle GoldenGate. • Lead the optimization of data pipelines and promote high-performance data engineering practices, with a focus on performance, scalability and proactive monitoring. • Ensure data quality and integrity through testing, validation and governance, collaborating with BI and data science teams. • Mentor junior data analysts and data engineers, fostering team growth and the adoption of data engineering best practices. • Foster innovation in the use of emerging technologies, such as machine learning and artificial intelligence, to apply predictive models and automation.

• Lead teams of data engineers and analytics professionals, providing technical direction and mentorship across the project lifecycle • Architect and implement cloud-native data platforms on AWS, designing schemas and ingestion pipelines that handle structured data from diverse sources including Excel feeds, legacy databases, and third-party systems • Design, develop, and maintain ETL/ELT pipelines using AWS Glue and Step Functions, ensuring reliable data transformation, validation, and quality enforcement at every stage • Own the infrastructure-as-code practice using Terraform — provisioning, versioning, and managing all cloud resources with full reproducibility and environment consistency • Deliver end-to-end reporting solutions through Power BI, translating complex data models into intuitive dashboards that provide stakeholders with actionable, near-real-time insights • Translate complex technical concepts and architectural decisions to non-technical stakeholders clearly and persuasively, facilitating informed decision-making at all levels • Establish and enforce best practices around data quality, pipeline monitoring, documentation, and incident response • Participate in pre-sales and discovery efforts, leveraging technical expertise to support scoping, estimation, and business development initiatives

• Plan, manage, and execute releases across all environments - from development to production. • Identify technical and functional interdependencies between various tracks. • Coordinate with all development pods and stakeholders across programs. • Review application code, documentation, and perform pre/post deployment tasks. • Define release process for new data engineering applications. • Change management communication to all required stakeholders. • Execute release packages, step-by-step deployment guides, and command line instructions on production environment. • Support project timelines, clearly setting expectations, and realigning expectations internally as priorities change. • Develop a sound understanding of client’s needs: data conversion and migration requirements, environment management and build processes, deployment planning and execution, solution designs, systems integrations, technical architectures, and infrastructure architectures.