Staff Data Engineer

This is a fully remote position, open to applicants in New York.

📋 Description

• Take charge of the architecture and design of data ingestion pipelines, orchestration frameworks, and data delivery systems.

• Create design documentation that can be implemented by DE2s, DE3s, and senior engineers.

• Define and enhance frameworks, conventions, and reference patterns for pipelines, Airflow DAGs, testing, monitoring, and catalog registration.

• Lead the identification and resolution of novel data integrity, performance, and reliability issues.

• Drive systematic improvements and transform recurring failures into runbooks, automation, or enhanced designs.

• Establish and monitor reliability standards, including SLOs, alerting mechanisms, and on-call health metrics.

• Minimize operational toil.

• Spearhead data security and governance strategies in collaboration with Security, Legal, and Compliance teams.

• Design reverse ETL and data delivery integrations with well-defined SLAs, downstream impact analysis, and failure-handling assurances.

• Guide platform decisions regarding Snowflake, Databricks, and AWS, focusing on cost optimization, capacity planning, and build-versus-buy assessments.

• Lead specification and design reviews while also reviewing high-risk pull requests.

• Collaborate with BI, Data Science, Product, and business leadership to develop scalable solutions and the project roadmap.

• Mentor engineers, represent the team in cross-functional discussions, address technical debt, and engage in hiring processes.

⛳️ Requirements

• 8+ years of professional experience in software or data engineering, with substantial experience managing production data platforms at scale.

• Proven history of designing and delivering large-scale, cross-team data systems from vague requirements to production implementation.

• Proficient in Python and SQL, with extensive experience in ETL/ELT patterns for complex, high-volume transformations.

• In-depth knowledge of Airflow / Managed Workflows for Apache Airflow, including DAG design at scale and operational best practices.

• Strong understanding of pipeline fundamentals: idempotency, backfills, schema evolution, late-arriving data, data quality frameworks, and failure recovery.

• Practical experience with a variety of tools including Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, and PostgreSQL.

• Experience in creating data security and governance capabilities, including PII masking, RBAC, catalog lineage, and reusable pipeline frameworks.

• Strong practices in testing, CI/CD, and code review.

• Demonstrated ability to mentor engineers, influence without formal authority, and foster alignment across teams.

• Exceptional written and verbal communication skills, including the ability to produce design documentation, conduct tradeoff analysis, and write incident reports.

🏝️ Benefits

• Base salary and bonus.

• Full-time employment.

• Benefits information available at https://benefitsatfanatics.com/.

• Opportunity for in-person onboarding through Launching into Better: LIVE—a multi-day cultural immersion in New York City.

• Possibility of onsite interviews, depending on the role and location.