Database Administrator

Brillient Corporation

. Design, build, and maintain ETL processes moving data into the Compliance Data Warehouse (CDW) .

Posted 10/15/2026full-timeSpring • Texas • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in ETL development, data analysis, and machine learning, with strong proficiency in SQL, Python, and statistical modeling. Capable of building scalable data pipelines and presenting technical findings to diverse audiences.

Highest-signal resume keywords

ETL DevelopmentSQL ScriptingPython ProgrammingMachine Learning Model EvaluationData Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL ProcessesSQLPythonStatistical AnalysisMachine LearningData CleaningFeature EngineeringShell ScriptingData TransformationPredictive Modeling

Soft Skills

Strong CommunicationCollaborationIndependent WorkProblem SolvingFast-Paced Environment Adaptability

Tools & Technologies

Sybase IQPostgresJupyter NotebookOpenShiftKubernetesApache AirflowGitDBeaverVS CodeSecureCRT

Certifications & Qualifications

Bachelor's Degree in Data SciencePublic Trust Security Clearance

Industry Keywords

Data WarehouseData QualityData ScienceMachine LearningExploratory Data AnalysisMLOpsAI TechnologiesContainerized EnvironmentsStatistical TechniquesData Pipelines

Tech Stack

Tools & technologies

AirflowApacheCloudETLKubernetesLinuxNumpyOpenShiftPandasPerlPostgresPythonScikit-LearnShell ScriptingSQLUnix

About the role

Key responsibilities & impact

Design, build, and maintain ETL processes moving data into the Compliance Data Warehouse (CDW)
Apply statistical and machine learning techniques to produce predictive models and actionable insights
Support CDW operations within RAAS through data analysis, process improvement recommendations, and research and evaluation of emerging technologies
Extract data and tables from Unix/Linux systems and transform and load them into Sybase IQ and Postgres
Refactor existing ETL jobs and build new solutions
Build an object-oriented, Unix-based framework of scripts and stored procedures to run and monitor ETL and statistics processes
Develop and run shell, SQL, and Python scripts for 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
Prepare, clean, transform, and explore data; engineer features 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
Validate model results, assess performance, and improve accuracy and reliability
Conduct exploratory and statistical analysis for data-driven decision-making
Develop and document analytical workflows and models in Jupyter Notebook
Optimize ETL processes and resolve performance bottlenecks and failures
Validate, cleanse, and audit data; collaborate with Data Quality to resolve inconsistencies
Work with Data Architects to design data models and schemas
Translate business and mission requirements into ETL and analytical solutions
Document ETL processes, workflows, data dictionaries, methodologies, models, assumptions, and results
Help users move data into Sybase IQ and provide metadata for the metadata repository
Present technical findings to technical and non-technical audiences
Participate in Scrum and client meetings and maintain Kanban board cards
Work in Linux/Unix and Windows environments, including OpenShift, Kubernetes, containerized, and distributed platforms
Monitor emerging ETL, data science, ML, and AI technologies and recommend process and infrastructure improvements

Requirements

What you’ll need

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, or a related technical field
US citizenship
Ability to obtain and maintain a Public Trust security clearance
At least eight (8) years of combined professional experience in ETL development and data science, analytics, or machine learning
Strong SQL ETL experience, focused on load, select, and update commands
High proficiency in Linux/Unix, Sybase IQ, and Sybase SQL scripting
Working experience with Postgres and Postgres SQL scripting
Strong hands-on Python experience for ETL, data analysis, and machine learning, including Pandas, NumPy, and Jupyter Notebook
Demonstrated experience building and evaluating ML models with scikit-learn or comparable frameworks
Experience with data cleaning, transformation, EDA, feature engineering, and model evaluation
Shell scripting for automation and data processing (KSH, Bash, SSH, sed, awk)
Experience working in Linux and Windows environments
Experience with OpenShift and/or Kubernetes
Strong communication skills, and the ability to work both independently and collaboratively in a fast-paced environment
Preferred: Experience with AI, LLMs, Retrieval-Augmented Generation (RAG), or model fine-tuning
Preferred: Experience with Apache Airflow and automated ETL pipelines
Preferred: Experience with SAP Data Services or other COTS ETL tools
Preferred: Experience with Git/GitLab, DBeaver, VS Code, SecureCRT/SecureFX, Wiki, JSON, and Perl
Preferred: Experience deploying ML models in containerized or cloud environments
Preferred: Experience with MLOps: model deployment, monitoring, and lifecycle management