Senior IT Data Engineer//

TITLE - Senior IT Data Engineer

Local to DC metro

100% ONSITE in Washington DC

Contract on W2 or 1099 only No c2c

Overview of the Role: The Senior IT Data Engineer is responsible for designing, building, and optimizing scalable data architectures, integration pipelines, and enterprise data platforms that support analytics, reporting, and operational decision-making. This role partners with business stakeholders, analysts, and technical teams to ensure data is accessible, reliable, secure, and structured to meet organizational needs. The ideal candidate brings deep hands-on expertise in data engineering, strong knowledge of database technologies, and the ability to translate complex data requirements into high-performing technical solutions.

Responsibilities

Design, develop, and maintain scalable data pipelines, ETL/ELT workflows, and integration processes across multiple data sources.

Build and optimize enterprise data models, databases, data warehouses, and cloud-based storage solutions to support reporting and analytics.

Ensure data quality, integrity, availability, and security through validation, monitoring, troubleshooting, and performance tuning.

Collaborate with analysts, economists, researchers, developers, and business stakeholders to gather requirements and deliver effective data solutions.

Implement workflow orchestration and automation tools to streamline data movement and processing.

Support migration of data pipelines and workloads between on-premises and cloud environments.

Develop and maintain scripts, services, and reusable components using Python, SQL, and other relevant programming languages.

Perform root cause analysis of data and process issues and recommend improvements to architecture, performance, and governance.

Create and maintain technical documentation, standards, and best practices for data engineering and platform operations.

Provide technical leadership and mentorship to junior team members while promoting DataOps, CI/CD, and engineering best practices.

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field; advanced degree preferred.

Typically requires 7+ years of experience in data engineering, data architecture, or a related technical role.

Advanced proficiency in SQL and experience with relational database platforms such as PostgreSQL, Microsoft SQL Server, and MySQL.

Strong hands-on experience with Python and familiarity with additional scripting or programming languages such as R, Java, Scala, or JavaScript.

Experience designing and supporting large-scale data platforms, including data warehouses, data lakes, and enterprise information architecture.

Demonstrated expertise in ETL/ELT design, workflow orchestration, and pipeline automation tools such as Apache Airflow, Prefect, Dagster, or similar technologies.

Experience working with cloud platforms and modern data technologies such as AWS, Azure, Snowflake, NoSQL databases, and CI/CD pipelines.

Strong understanding of data modeling, performance optimization, data governance, and secure data handling practices.

Excellent analytical, troubleshooting, communication, and collaboration skills.

Experience supporting analytics, research, or data-intensive business environments is strongly preferred.

Citizenship Requirement: Yes Work

Experience:

The Data Architecture, Technology, and Analytics (DATA) section is tasked with transforming how the Federal Reserve Board's Division of Research & Statistics (R&S) ingests, organize, uses, and visualizes data.

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.

Technical 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.

Ayush Sharma Sr. US Technical Recruiter

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