Senior Data Architect

Overview - The Organization is modernizing legacy data environments by transforming fragmented and proprietary databases into integrated cloud-based data platforms, enterprise data integration systems, and secure collaboration tools. These initiatives are designed to improve data accessibility, scalability, and security while enabling advanced analytical capabilities for economic forecasting and policy development.

To support this transformation, the Organization seeks an experienced and detail-oriented Senior Data Architect / Modeler to lead the design, development, and optimization of modern data architectures and pipelines. The ideal candidate is a hands-on data professional with deep expertise in data modeling, database architecture, ETL/ELT development, and scalable data engineering solutions.

Key Responsibilities

·        Analyze existing data processes, applications, and source systems to identify dependencies, data quality issues, and business rules affecting enterprise data management.

·        Review, optimize, and modernize current data models and architectures.

·        Design, develop, and maintain scalable data pipelines that ingest, transform, and deliver data from multiple sources to analytics platforms.

·        Architect and implement ETL/ELT workflows supporting large-scale economic and research data processing.

·        Develop conceptual, logical, and physical data models aligned with enterprise data strategy and research requirements.

·        Define and implement database structures, backup and recovery procedures, and data security controls.

·        Maintain documentation including data dictionaries, metadata, and data flow diagrams.

·        Collaborate with business and research teams to enhance data accessibility, analytics, and visualization capabilities.

·        Implement data quality monitoring processes to ensure reliability, accuracy, and availability of enterprise data.

·        Identify and implement automation, scalability, and performance improvements across data infrastructure and delivery processes.

Required Qualifications

·        10 years of professional experience in data architecture, data modeling, or data engineering roles, with expertise in SQL and relational databases including PostgreSQL, Microsoft SQL Server, and MySQL.

·        Strong programming skills in Python, R, and related scripting languages.

·        Hands-on experience designing and managing scalable databases, enterprise data platforms, and high-volume data pipelines.

·        Proven experience developing and automating ETL/ELT workflows and data integration solutions.

·        Experience with workflow orchestration tools such as Apache Airflow, Prefect, Dagster, or AWS Step Functions.

·        Experience supporting cloud and hybrid data environments using AWS, Azure, Snowflake, or similar technologies.

·        Experience with Linux environments and source control platforms such as GitLab and GitHub.

·        Ability to design and communicate enterprise data architecture across conceptual, logical, and physical layers with experience in large-scale data processing, and data lake architectures.

·        Experience migrating data workflows between on-premises and cloud environments with knowledge of structured and unstructured data integration techniques.

·        Experience with NoSQL and graph database technologies.

·        Understanding of time-series data, forecasting methodologies, and economic or financial datasets.

·        Experience implementing Change Data Capture (CDC), CI/CD pipelines, and DataOps practices.

·        Familiarity with machine learning model development and deployment.

·        Working knowledge of Java, Scala, JavaScript, Perl, or related programming languages.

·        Experience working in research, economic policy, or financial services environments.

·        Bachelor’s degree in Computer Science or related sciences

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