Lead Databricks Integration Analyst

Job description

Shape the future of enterprise data integration! Are you passionate about building scalable data integrations that power business decisions? Do you enjoy solving complex data challenges while influencing technical direction? If so, we want to hear from you! We are seeking a Lead Databricks Integration Analyst to help design, build, and operate the data integration layer connecting enterprise sales applications to our Databricks Lakehouse platform.

You'll partner with architects, engineers, application teams, and business partners to deliver reliable, governed, and scalable data pipelines while serving as a technical leader across our sales integration portfolio. This position is in Richmond, VA with a Hybrid work schedule. Relocation benefits are available.

What you will be doing

Designing and implementing bi-directional integrations between enterprise sales applications and the Databricks Lakehouse using Databricks-native and Azure integration technologies. Building, configuring, and optimizing ingestion pipelines for databases, SaaS platforms, file feeds, and streaming data, including change data capture, incremental processing, and schema evolution. Developing and maintaining transformation pipelines using native Databricks integration tooling (i.e.

Spark Declarative Pipelines, Lakeflow Jobs, and Lakehouse Connect), leveraging built-in quality controls, dependency management, and scalable processing patterns. Establishing and enforcing data quality standards, monitoring, logging, operational support processes, and incident resolution practices for production pipelines. Partnering with application owners, vendors, and platform teams to establish connectivity, authentication, data contracts, and integration standards.

Leading integration initiatives by providing technical direction, conducting design and code reviews, and mentoring team members on Databricks integration practices. Translating business requirements into scalable technical solutions while effectively communicating priorities, risks, tradeoffs, and progress to technical and non-technical partners.

We want you to have: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field, and 6+ years of directly related professional experience designing, developing, and supporting enterprise data integrations and data pipelines in production environments. 3+ years of hands-on experience with Databricks, including designing, building, and operating data ingestion and transformation pipelines.

Experience with Lakeflow Connect, including connector configuration, change data capture (CDC), incremental ingestion, and troubleshooting production integration issues. Experience developing and operating Lakeflow Jobs and multi-step workflow orchestration, including scheduling, dependency management, retries, monitoring, and alerting. Experience building Spark Declarative Pipelines, including streaming or incremental processing and embedded data quality controls.

Strong SQL and Python development skills, including experience tuning and troubleshooting Spark workloads.

Preferred

Experience with medallion architecture, Unity Catalog, CI/CD and infrastructure-as-code practices, automated pipeline testing, Azure cloud services, Agile Project Delivery and leading technical projects or mentoring other engineers.