Senior Data Engineer / Data Scientist

Fully Remote • IRS Remote (job post use) - Reston, VA 20190

• Level: Experienced

Location: Remote-DC, FL, KS, MD, MO, TX, VA
Work Arrangement: 100% Remote
Employment Type: Full-Time
Salary Range: $120,000-$140,000 annually
Citizenship: U.S. Citizenship Required
Security Requirement: Must be able to obtain and maintain a Public Trust determination.

Brillient Corporation is seeking an experienced Senior Data Engineer / Data Scientist to support a mission-critical IRS data warehousing initiative. This position combines ETL engineering and data science responsibilities, including designing and maintaining data pipelines for the Compliance Data Warehouse (CDW) and developing predictive models and actionable insights through statistical analysis and machine learning.

The position supports CDW operations within Research, Applied Analytics and Statistics (RAAS), providing technical expertise in data analysis, process improvement, and evaluation of emerging technologies to enhance data availability, analytics, and value to stakeholders.

The CDW is a large-scale data warehouse containing IRS return, entity, information return, regulatory, enforcement, web, and security data. The team supports ETL development, database administration, SQL and Bash development, SAS administration, system security, metadata, data quality, and intergovernmental data exchanges.

The ideal candidate brings strong hands-on data engineering and data science experience, with the ability to develop scalable ETL solutions, analyze complex datasets, and deliver reliable analytical solutions within a federal data environment.

Key Responsibilities

Data Engineering & ETL Development

• Extract data and tables from Unix/Linux systems and transform and load them into Sybase IQ and PostgreSQL.
• Refactor existing ETL jobs and develop new solutions, including object-oriented, Unix-based frameworks of scripts and stored procedures to execute and monitor ETL and statistical processes.
• Develop and execute shell, SQL, and Python scripts to support data processing, automation, and analytical workflows.
• Build repeatable, scalable data pipelines and analytical processes.
• Troubleshoot shell and SQL errors and configure and operate SSH clients across servers.

Data Science & Analytics

• Prepare, clean, transform, and explore data, including feature engineering using Pandas and NumPy.
• Analyze large, complex datasets to identify trends, patterns, relationships, and actionable insights.
• Develop, implement, evaluate, and maintain statistical and machine learning models using scikit-learn or comparable frameworks.
• Validate model results, assess performance, and improve accuracy and reliability.
• Conduct exploratory and statistical analysis to support data-driven decision-making.
• Develop and document analytical workflows and models using Jupyter Notebook.
• Work with structured and unstructured data from multiple sources and formats.

Optimization, Performance & Data Quality

• Optimize ETL processes to ensure efficient and timely data processing.
• Monitor ETL jobs and resolve performance bottlenecks and failures.
• Maintain data accuracy and integrity through validation, cleansing, and auditing.
• Collaborate with the Data Quality team to identify and resolve data inconsistencies.

Collaboration & Documentation

• Partner with Data Architects to design data models and schemas that meet business requirements.
• Translate business and mission requirements from analysts, subject matter experts, and stakeholders into ETL and analytical solutions.
• Document ETL processes, workflows, data dictionaries, methodologies, models, assumptions, and results.
• Support users in loading data into Sybase IQ and providing metadata for the metadata repository.
• Communicate complex technical findings to both technical and non-technical audiences.
• Participate in Scrum and client meetings and maintain current Kanban board activities.

Environment & Continuous Improvement

• Work across Linux/Unix and Windows environments, including containerized and distributed platforms such as OpenShift and Kubernetes.
• Evaluate emerging ETL, data science, machine learning, and AI technologies and recommend improvements to processes and infrastructure.

What We Offer

• Fully remote work flexibility
• Generous paid time off
• Medical, dental, and vision insurance
• Company-paid life insurance and short-term disability coverage
• Voluntary life insurance and long-term disability coverage
• Employee Assistance Program (EAP)
• Wellness programs
• 401(k) retirement plan
• Competitive compensation

Equal Employment Opportunity and Accommodations

Brillient is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable law.

Brillient is committed to providing reasonable accommodations to individuals with disabilities throughout the application and interview process.

Qualifications

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, or a related technical field.
• Minimum of eight (8) years of combined professional experience in ETL development and data science, analytics, or machine learning.
• Strong SQL and ETL experience, including load, select, and update commands.
• High proficiency in Linux/Unix, Sybase IQ, and Sybase SQL scripting.
• Working experience with PostgreSQL and PostgreSQL scripting.
• Strong hands-on Python experience supporting ETL, data analysis, and machine learning, including Pandas, NumPy, and Jupyter Notebook.
• Demonstrated experience developing and evaluating machine learning models using scikit-learn or comparable frameworks.
• Experience with data cleaning, transformation, exploratory data analysis (EDA), feature engineering, and model evaluation.
• Experience with shell scripting and automation, including KSH, Bash, SSH, sed, and awk.
• Experience working in Linux/Unix and Windows environments.
• Experience with OpenShift and/or Kubernetes.
• Strong analytical, problem-solving, and communication skills, with the ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications

• Experience with artificial intelligence (AI), large language models (LLMs), Retrieval-Augmented Generation (RAG), or model fine-tuning.
• Experience with Apache Airflow and automated ETL pipelines.
• Experience with SAP Data Services or other commercial off-the-shelf (COTS) ETL tools.
• Experience with Git/GitLab, DBeaver, VS Code, SecureCRT/SecureFX, Wiki platforms, JSON, and Perl.
• Experience deploying machine learning models in containerized or cloud environments.
• Experience with MLOps, including model deployment, monitoring, and lifecycle management.

Location & Security Requirements

• This is a 100% remote position. Candidates must reside in Washington, DC; Florida; Kansas; Maryland; Missouri; Texas; or Virginia.
• U.S. citizenship is required.
• Must be able to obtain and maintain a Public Trust determination.

The selected candidate must successfully complete the required federal background investigation and Public Trust suitability process prior to starting employment. This process may take up to 90 days, and the anticipated start date is contingent upon successful completion.