Key skills
Cloud Data WarehousingStreaming Data ProcessingSoftware Development FundamentalsDatabase ExpertisedbtPipeline Orchestration EnginesChange Data CaptureDecisive & AdaptableAI-assisted Coding ToolsProject Management ToolsCommunication SkillsOrganizational SkillsProject Management SkillsAIMLData WarehousingSnowflakeRedshiftKafkaAirflowApache AirflowPostgreSQLElasticsearchVersion ControlSaaSJiraProject ManagementCommunicationDecision Making
About this role
Lob is transforming the way businesses use direct mail through innovative technology. The Staff Data Engineer will lead the design and buildout of a unified event tracking platform, collaborating with various teams to enhance Lob's data ecosystem and mentor fellow engineers.
Responsibilities:
- Collaborate with colleagues in the Data, Product, and Engineering teams to unify Lob’s foundational data ecosystem and enable the buildout of internal and external data products
- Create modular, reusable frameworks to enable other engineering teams to publish events to the unified platform
- Implement thorough monitoring and alerting to ensure the health of the data platform
- Apply software development best practices to ensure maintainability of the platform
- Partner with the Engineering Manager to set the Data team’s roadmap & define team processes
- Coach and mentor mid-level engineers on the Data team regarding technical best practices and problem-solving
- Create and maintain documentation for data products and systems
- Advise stakeholders on the constraints and assumptions of the data processed through the unified data platform
- Deprecate outdated legacy systems without negatively impacting core functionality for end users
- Monitor Cloud and SaaS spend for unusual spikes and seek out opportunities to save costs
- Participate in the team on-call rotation (approximately 1 in 4 weeks). Triage and resolve alerts as needed
- Coordinate with other Staff+ engineers on the broader the tech team to align decision making and execute strategic initiatives
Requirements:
- Bachelor's or Master's degree in a quantitative field, or equivalent work experience
- At least 8 years (but preferably 10 or more) of combined experience in Data, ML, and/or Software Engineering
- Expertise in Cloud Data Warehousing (Snowflake strongly preferred, Redshift is a plus)
- Expertise in streaming data processing systems such as Kafka and Apache Flink
- Expertise in modern software development fundamentals including APIs, version control, containerization, and CICD
- Expertise in a variety of database types, including transactional databases (PostgreSQL preferred) and document/vector databases (like Elasticsearch), with ability to select the right tool for a given job
- Familiarity with dbt (data build tool)
- Familiarity with pipeline orchestration engines (Apache Airflow or Prefect preferred)
- Familiarity with Change Data Capture (CDC) patterns and methods
- Excellent verbal, written, and visual communication skills
- Excellent organizational and project management skills
- Ability to be decisive & adaptable in the face of ambiguity
- Experience with AI-assisted coding tools like ClaudeCode or Cursor
- Proficient with project management tools including Jira