Senior Data Architect / Data Engineer - 26-06256
About The Position
We are seeking a highly experienced Senior Data Architect / Data Engineer to support a large-scale data modernization initiative focused on transforming legacy data environments into modern cloud-based analytical platforms. This role will be responsible for designing, developing, and optimizing enterprise data architectures, scalable ETL/ELT pipelines, and advanced analytics infrastructure to support economic forecasting, policy research, and enterprise reporting initiatives. The ideal candidate is a hands-on technical expert with deep experience in enterprise data engineering, cloud technologies, workflow orchestration, database architecture, and large-scale data integration. This individual will collaborate closely with research teams, data analysts, architects, and business stakeholders to improve data accessibility, scalability, governance, and operational efficiency.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or related technical field
- Minimum 7+ years of experience in Data Architecture, Data Engineering, or related technical roles
- Strong hands-on experience designing enterprise data platforms and data integration solutions
- Experience building and maintaining large-scale ETL/ELT pipelines
- Experience with cloud migrations and modern data infrastructure implementations
- Advanced SQL development
- Python and/or R scripting
- Relational databases including: PostgreSQL, Microsoft SQL Server, MySQL
- Workflow orchestration tools such as: Apache Airflow, Prefect, Dagster
- Source control platforms: GitHub, GitLab
- Linux-based development environments
- Data modeling and database optimization
- Data quality and governance practices
- Experience with one or more: Amazon Web Services, Microsoft Azure, Snowflake
Nice To Haves
- Advanced degree preferred
- Experience working with economic, financial, or research datasets
- Experience with time-series data and forecasting analytics
- Experience implementing Change Data Capture (CDC) methodologies
- Experience with NoSQL or graph database technologies
- Experience with machine learning model deployment and maintenance
- Experience implementing CI/CD pipelines and DataOps practices
- Knowledge of Java, Scala, JavaScript, or Perl
- Experience supporting enterprise analytics and visualization platforms
Responsibilities
- Design, develop, and maintain scalable enterprise data architectures and analytical platforms
- Build and optimize robust ETL/ELT pipelines for ingesting, transforming, and delivering structured and unstructured data
- Develop scalable database solutions, data lakes, and enterprise data platforms
- Create conceptual, logical, and physical data models aligned with business and research objectives
- Implement data integration strategies across multiple on-premises and cloud-based systems
- Design and automate data workflows using modern orchestration tools
- Develop scalable data processing frameworks for high-volume datasets
- Optimize data flows, database performance, and pipeline efficiency
- Implement monitoring, validation, and data quality controls across all data systems
- Support migration of legacy systems and workflows to modern cloud platforms
- Implement scalable cloud-native data solutions and automation frameworks
- Collaborate on enterprise modernization and DataOps initiatives
- Assist with CI/CD implementation and deployment automation for data platforms
- Design and maintain relational and enterprise database structures
- Develop backup, recovery, and access security procedures
- Maintain metadata documentation, data dictionaries, and technical specifications
- Ensure data integrity, governance, and compliance standards are maintained
- Partner with economists, analysts, technical teams, and business stakeholders
- Translate complex business requirements into scalable technical solutions
- Provide technical leadership and recommendations for future-state architecture
- Support analytics, visualization, and reporting initiatives
- Identify opportunities for automation and operational efficiency improvements
- Conduct root cause analysis for data and system-related issues
- Contribute to enterprise data architecture standards and best practices
- Support adoption of advanced analytics and machine learning capabilities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
