Data Engineer

Amivero•,

21d

About The Position

The Amivero Team Amivero’s team of IT professionals delivers digital services that elevate the federal government, whether national security or improved government services. Our human-centered, data-driven approach is focused on truly understanding the environment and the challenge, and reimagining with our customer how outcomes can be achieved. Our team of technologists leverage modern, agile methods to design and develop equitable, accessible, and innovative data and software services that impact hundreds of millions of people. As a member of the Amivero team you will use your empathy for a customer’s situation, your passion for service, your energy for solutioning, and your bias towards action to bring modernization to very important, mission-critical, and public service government IT systems. Special Requirements US Citizenship required to obtain Public Trust DHS ICE Public Trust preferred Master Degree +9 years of experience OR Bachelor Degree +12 years of experience The Gist… We are seeking a skilled Data Engineer with strong Databricks experience to design, build, and support modern data pipelines and data platform solutions. This role is ideal for someone who is hands-on, detail-oriented, and comfortable working with data engineering tools, ETL/ELT processes, data quality controls, and the Databricks ecosystem. The Data Engineer will work closely with architects, customers, business stakeholders, analysts, and technical teams to build scalable data pipelines, support Databricks environments, implement governance controls, and help deliver reliable data solutions. This person should have experience working with Databricks, Unity Catalog, ETL pipelines, data quality frameworks, and cloud-based data platforms, with exposure to emerging Databricks capabilities such as Unity Catalog AI Gateway and Agent Bricks

Requirements

Hands-on experience as a 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.
US Citizenship required to obtain Public Trust

Nice To Haves

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.
DHS ICE Public Trust preferred

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.