Description

The Data Architecture, Technology, and Analytics (DATA) section is looking for an experienced detailed oriented Data Architect/Engineer who will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for economic policy and research teams. The ideal candidate is an experienced hands-on data modeler with working knowledge of database design and administration, data pipeline building, and data wrangling who enjoys improving existing data systems and/or building them from the ground up. The Data Architect/Engineer will support our economists and technical experts and will ensure optimal data delivery architecture is designed and developed. They must have a service mindset, be self-directed, and be comfortable supporting the data needs of multiple teams and systems. The right candidate will be excited by the prospect of optimizing or even re designing the R&S division’s data architecture to support our next generation of data initiatives.

REQUIREMENTS:  

The candidate shall possess the knowledge and skills set forth in the Technical Services BOA,

Section 3.5.9.2 for labor category Senior Data Architect.

The candidate shall also demonstrate the below knowledge and experience:

• Analyze data processes, applications, and source data to understand dependencies, anomalies,

and implicit business rules that impact the division’s ability to manage data. Review and

analyze existing data models and processes to optimize and modernize current data

architectures.

• Design, develop, and maintain robust data pipelines that ingest, transform, and deliver data

from multiple sources to analytics platforms, ensuring optimal performance and data integrity

throughout the process.

• Architect and implement ETL/ELT workflows using modern data engineering tools and

frameworks to support large-scale data processing for economic analysis.

• Create data solution designs for economic policy and research projects, including conceptual

models, integration models, and sourcing strategies, in alignment with the division’s research

needs and data strategy. Translate division and section requirements into long-term

information architecture solutions.

• Define specifications and implement database structures, including logical and physical data

models, backup and recovery procedures, and access security controls. Develop and maintain

formal documentation of data structures, data flows, data dictionaries, and technical

metadata.

• Collaborate with research and business teams to improve data models and data processes that

support analytics and visualization tools, increasing data accessibility and fostering data

driven decision making across the organization.

• Implement processes and systems to monitor data quality, ensuring production data is

accurate, reliable, and available for end users and dependent business processes.

• Identify, design, and implement internal process improvements, including automation of

manual processes, optimization of data delivery, and redesign of infrastructure to improve

scalability and performance.

• Participate in the development of future-state data architecture standards, guidelines, and

Principles.

Specific Requirements and Skills 

• Bachelor’s degree in computer science, Information Technology, Engineering or a related

technical field and at least 7 years of related experience; advanced degree preferred.

• Advanced working knowledge of SQL and experience working with relational database

platforms including PostgreSQL, Microsoft SQL Server, and MySQL.

• Advanced working knowledge of Python, R, and other scripting languages used for data

engineering and analytics.

• Experience working with large-scale data systems, including distributed computing, scalable

data processing, data storage architecture, and optimization of high-volume data workloads.

• Experience designing, developing, and automating ETL/ELT workflows and data integration

pipelines.

• Experience building, optimizing, and maintaining scalable databases, data pipelines and data

processing frameworks.

• Experience with workflow orchestration and pipeline automation tools such as Apache

Airflow, Prefect, Dagster, or AWS Step Functions.

• Experience migrating workflows and data pipelines between on-premises and cloud

environments.

• Experience processing, analyzing, and integrating structured and unstructured data sources.

• Experience developing in Linux environments and using source control platforms such as

GitLab and/or GitHub.

• Experience performing root cause analysis on internal and external data and business

processes to answer business questions and identify opportunities for improvement.

• Ability to design and communicate enterprise information architecture at conceptual, logical,

and physical levels.

• In-depth experience designing and implementing database, data lake, and enterprise data

platform solutions.

• Strong hands-on software engineering and implementation experience, including

development, testing, and deployment of data applications and services.

• Excellent oral and written communication skills with a strong customer service orientation.

• Exceptional analytical, problem-solving, and troubleshooting skills. 

Understanding of time series data and related analytical and forecasting techniques.

• Experience working in a research environment and/or with economic or financial data.

• Experience with NoSQL and graph database technologies.

• Experience developing, training, deploying, and maintaining machine learning models.

• Working experience with cloud technologies such as AWS, Microsoft Azure, and Snowflake.

• Experience implementing data warehouses utilizing Change Data Capture (CDC)

methodologies.

• Experience implementing and maintaining CI/CD pipelines and DataOps platforms.

• Working knowledge of additional programming and scripting languages such as Java, Scala,

JavaScript, or Perl

Key Skills

Education

Bachelor's degree