Data Architect/ Science Lead

Amivero•Camp Springs, MD

3d•Onsite

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.

Requirements

US Citizenship Required to obtain a Public Trust
Bachelor Degree and 10 years enterprise data architecture, AI/ML, data engineering, and data experience
Must be local to the DMV area
Bachelor Degree and 10 years of experience supporting enterprise data architecture, data engineering, analytics, AI/ML, and data management initiatives.
Experience leading enterprise system integration, data migration, transformation, data warehouse, data mart, data lake, lakehouse, and operational support initiatives within large organizations.
Experience developing, deploying, evaluating, and maintaining production AI/ML solutions utilizing AWS and Databricks platforms.
Experience utilizing Databricks, Spark/Scala, Python, SQL, NumPy, PyTorch, Scikit-Learn, and advanced analytics frameworks to develop machine learning and data science solutions.
Proven expertise in relational data modeling, dimensional data modeling, data warehouse design, and enterprise data architecture.
Experience designing and supporting enterprise data platforms utilizing PostgreSQL, Oracle, SQL Server, Aurora, RDS, Redis, and OpenSearch.
Experience implementing real time and event driven data architectures utilizing Kafka, Confluent Kafka, Kinesis, and related streaming technologies.
Experience developing data visualization, reporting, and business intelligence solutions utilizing Tableau, Kibana, Splunk, and related analytics platforms.
Experience supporting cloud based data architectures utilizing AWS services including S3, Lambda, Kinesis, OpenSearch, Aurora, CloudWatch, and CloudFormation
Advanced proficiency in statistical analysis, predictive modeling, data mining, data engineering, and machine learning methodologies.
Experience conducting technical assessments, architecture reviews, and cost benefit analyses to support technology selection and modernization initiatives.

Responsibilities

Lead the design, implementation, and governance of enterprise data architecture supporting structured, semi structured, and unstructured data environments.
Architect and oversee the development of enterprise data warehouses, data marts, data lakes, lakehouse environments, and analytics platforms.
Lead large scale data migration, transformation, integration, modernization, and operational support initiatives.
Design and implement scalable data pipelines supporting data ingestion, processing, transformation, and analytics.
Develop and evaluate machine learning models, artificial intelligence solutions, predictive analytics capabilities, and advanced statistical models.
Collaborate with business stakeholders, architects, engineers, and program leadership to identify data driven solutions supporting mission objectives.
Establish enterprise data governance standards, data quality processes, metadata management practices, and master data management strategies.
Conduct technical evaluations and cost benefit analyses of competing technologies, architecture, and implementation approaches.
Develop dashboards, reporting solutions, and data visualization capabilities that support executive decision making.
Provide technical leadership and mentoring to data engineers, data scientists, database administrators, and analytics teams.
Ensure compliance with federal data security, privacy, and governance requirements.