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The Matlen Silver Group, Inc. in Plano, TX is seeking a Senior Data Solutions Architect to drive analytics across the enterprise data platforms in a banking environment.
You will design scalable data models, optimize capacity, and automate reporting for the data warehouse and data lake ecosystem. Candidates demonstrate deep Hadoop expertise (HDFS, Hive, Impala, YARN), API-driven ETL with PySpark, and hands-on experience with Cloudera Manager, Tableau, and Power BI for executive visibility.
Location Plano, United States Sector Banking
The Senior Data Solutions Architect for the Enterprise Data Platforms Advanced Analytics team drives enterprise-wide capacity management, resource optimization, and data platform insights by building analytics solutions within the Enterprise Data Warehouse and enterprise data lake ecosystem. This role will contribute to building a single source of truth for capacity data, developing scalable data models, automating reporting, and enabling data-driven decision-making for storage, compute, onboarding demand, and platform hygiene initiatives across enterprise platforms.
Success in this role requires a highly proactive, self-motivated individual who can work independently and demonstrates deep Hadoop architectural expertise, including HDFS, FSImage analysis, Ozone, Hive, Impala, YARN, compute resource analysis, API-driven data integration, and the ability to develop pragmatic solutions.
A lead-level professional with a strong sense of ownership, results-oriented mindset, and the ability to independently drive complex initiatives to successful outcomes with minimal guidance.
Demonstrated expertise in designing and delivering analytics solutions across enterprise data lakes, large-scale Hadoop platforms, and cloud or hybrid data ecosystems.
Deep knowledge of HDFS, HBase, Ozone, MinIO, and Data Services leveraging HDFS CLI commands and FSImage analysis for storage and compute utilization assessment.
Familiar with object storage architectures, including bucket-based storage models and S3-compatible platforms.
Proficient in analyzing CPU, memory, and workload utilization across Hadoop platforms using YARN, Hive, and Impala query metrics for resource utilization reporting.
Experienced using Cloudera Manager, Pepperdata, and/or Acceldata Pulse for Hadoop platform monitoring and operational insights.
Proven hands-on experience developing API-driven ETL pipelines using cURL, PySpark, and shell scripting to extract, validate, and load data into Hive tables, with Autosys scheduling, monitoring, and error resolution.
Skilled in designing data models and developing analytical datasets to capture and analyze storage, compute, and resource utilization metrics across Hadoop and cloud platforms.
Ability to translate complex data into actionable insights for senior leadership and executive audiences.
Proficiency in Excel automation using VBA, Power Query, and scripting to streamline data refresh processes and improve reporting efficiency.
Familiar with visualization tools such as Tableau, and PowerBI or similar tools.
Experience working with advanced visualization such as Prometheus and Grafana to support platform visibility and trend analysis.
Passion for automation and process simplification, while maintaining the highest standards of data accuracy, integrity, and consistency.
Recognized for strong problem-solving skills, attention to detail, and a continuous improvement mindset, with the ability to work in a fast-paced environment.
Ability to lead proof-of-concept (POC) efforts for emerging technologies, evaluate business value, and recommend scalable implementation strategies.