Senior Data Engineer

Amivero is seeking a Senior Data Engineer to design, build, and support modern data pipelines and data platform solutions. The role focuses on Databricks, ETL/ELT processes, data quality and governance, and delivering reliable, scalable data solutions in collaboration with customer and technical teams.

Responsibilities:

• Build, develop, and maintain scalable data pipelines using Databricks
• Design and implement ETL/ELT processes to ingest, transform, validate, and deliver data
• Work with Databricks notebooks, workflows, jobs, clusters, Delta Lake, and Spark-based processing
• Support the implementation and management of Databricks environments
• Develop and optimize batch and streaming data pipelines
• Implement data quality checks, validation rules, reconciliation processes, and control frameworks
• Support data governance, access controls, metadata management, and lineage using Unity Catalog
• Work with architects to implement platform standards, engineering patterns, and best practices
• Support use cases involving Unity Catalog AI Gateway, Agent Bricks, and AI-enabled data solutions
• Troubleshoot data pipeline issues, performance problems, and production defects
• Monitor pipeline reliability, performance, and data accuracy
• Collaborate with customer teams to understand requirements and deliver technical solutions
• Participate in customer-facing discussions, technical workshops, demos, and implementation reviews
• Create and maintain technical documentation, including data flows, pipeline logic, data mappings, and operational procedures
• Work with cloud services and modern data platform tools to deliver secure, scalable, and reliable data solutions

Requirements:

• US Citizenship required to obtain Public Trust
• Master Degree +9 years of experience OR Bachelor Degree +12 years of experience
• Hands-on experience as a Senior Data Engineer or similar role
• Strong experience with Databricks and the broader Databricks ecosystem
• Experience building and maintaining ETL/ELT pipelines
• Strong knowledge of Apache Spark, PySpark, SQL, and Delta Lake
• Experience working with structured, semi-structured, and unstructured data
• Understanding of data quality, data validation, monitoring, and control processes
• Experience with Unity Catalog, including permissions, access control, metadata, and governance concepts
• Ability to support and work within architected Databricks environments
• Familiarity with cloud data platforms such as AWS, Azure, or Google Cloud Platform
• Strong SQL skills and experience optimizing queries and data transformations
• Ability to troubleshoot pipeline failures, performance issues, and data integrity problems
• Strong communication skills and ability to work directly with customers and stakeholders
• Ability to translate business and technical requirements into working data solutions
• DHS ICE Public Trust preferred
• Experience with API management and security (Mulesoft, Kong)
• Exposure to or experience with Unity Catalog AI Gateway
• Exposure to or experience with Agent Bricks
• Experience with Lakehouse architecture
• Experience with CI/CD pipelines and source control tools such as Git
• Experience with workflow orchestration tools and Databricks Workflows
• Experience with streaming technologies such as Spark Structured Streaming, Kafka, or Event Hubs
• Experience with data modeling, dimensional modeling, or medallion architecture
• Knowledge of security, privacy, data governance, and compliance practices
• Databricks certifications are a plus
• Consulting or customer-facing delivery experience is preferred