Lead Software Engineer I (DevOps, Azure, SQL, Nifi/ Dagster)

Develop and optimize SQL-based data solutions, including queries, transformations, and performance tuning for operational and analytical workloads.

Build and maintain CI/CD pipelines and DevOps automation to enable reliable, repeatable deployments across environments.

Lead Data Engineering & Orchestration by Design and implement data pipelines using: Dagster for orchestration, dependency management, and observability Apache NiFi for ingestion, routing, transformation, and system integrations Databricks for scalable data processing and transformations Ensure data pipelines meet standards for data quality, monitoring, and operational resilience.

Dagster for orchestration, dependency management, and observability

Apache NiFi for ingestion, routing, transformation, and system integrations

Databricks for scalable data processing and transformations

Ensure data pipelines meet standards for data quality, monitoring, and operational resilience.

Take ownership of day-to-day execution for the engineering team in an Agile (Scrum/Kanban) framework, ensuring predictable delivery and flow. Lead or actively drive Agile ceremonies, backlog refinement, estimation, and sprint planning. Work with Product Owners and stakeholders to set priorities, balance feature delivery with technical debt and operational needs, and manage dependencies.

Act as Technical Lead & Delivery Anchor. Coordinate and allocate work across engineers; provide technical guidance, code/design reviews, and delivery support. Identify risks early (performance, reliability, security, cost) and drive mitigation through design or implementation changes. Lead production issue analysis, root-cause investigations, and preventive actions to reduce recurring incidents.

Engage directly with business and technical stakeholders to clarify requirements, manage expectations, and communicate progress and trade-offs clearly. Build trust through transparent communication and reliable delivery.

Create and maintain high-quality documentation including architecture notes, pipeline designs, deployment procedures, and operational runbooks. Contribute to engineering standards and reusable patterns to improve consistency and supportability across teams.