

Veridian Tech Solutions, Inc.
Senior Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Engineer in Irving, TX/Wilmington, DE, with a contract length of over 6 months and a pay rate of "unknown." Requires 12+ years of experience in a regulated banking environment, expertise in Apache Spark, Cloudera, SQL, and GCP.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 27, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Irving, TX
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🧠 - Skills detailed
#Oracle #Data Architecture #GIT #SQL Server #Logging #Migration #GitHub #Cloudera #Jenkins #RDBMS (Relational Database Management System) #Apache Spark #SQL (Structured Query Language) #Metadata #PySpark #Documentation #YARN (Yet Another Resource Negotiator) #DevOps #"ETL (Extract #Transform #Load)" #Code Reviews #HDFS (Hadoop Distributed File System) #AI (Artificial Intelligence) #Hadoop #Automated Testing #Compliance #GCP (Google Cloud Platform) #MS SQL (Microsoft SQL Server) #Scala #Spark (Apache Spark) #Monitoring #Batch #Cloud #Data Engineering #Data Quality
Role description
Hi
Hope you are doing great!
Please share your resume if interested.
Role : Senior Data Engineer
Location : Irving, TX / Wilmington, DE (Onsite)
Hire type : Fulltime
Experienced Senior Data Engineer (12+ Years) to support large scale data platform modernization initiatives within a regulated banking environment.
The role focuses on designing and building enterprise-grade in-house frameworks, supporting high-volume batch and CDC-based incremental processing using Cloudera platform, and enabling ongoing Google Cloud Platform (GCP) modernization efforts.
Technology & Skill Requirements
• Apache Spark (PySpark and/or Scala) in large-scale production environments
• Cloudera Hadoop ecosystem (HDFS, Hive, YARN, Spark on Cloudera)
• Strong SQL expertise with complex transformations, performance tuning, and reconciliation logic
• Enterprise RDBMS experience with Oracle and MS SQL Server
• Batch ingestion, incremental ingestion, and CDC processing patterns
• CDC concepts and tooling (tool-agnostic: GoldenGate, Debezium, or equivalent)
• Data merge, deduplication, watermarking, checkpointing, and SCD handling
• Google Cloud Platform services including Dataproc , Composer and Dataplex
• Hybrid on prem to cloud data architecture and migration patterns
• Metadata-driven framework development and data quality validation techniques
• CI/CD pipeline implementation using enterprise tooling (GitHub Actions, Jenkins, DevOps)
• Git-based development workflows, code reviews, and automated testing practices
• Experience using Copilot or similar AI-assisted development tools safely and effectively in enterprise environments
• Logging, monitoring, alerting, and operational readiness practices
• Secure coding, access control, and compliance-aware development
• Documentation of design artifacts, runbooks, and operational procedures
Hi
Hope you are doing great!
Please share your resume if interested.
Role : Senior Data Engineer
Location : Irving, TX / Wilmington, DE (Onsite)
Hire type : Fulltime
Experienced Senior Data Engineer (12+ Years) to support large scale data platform modernization initiatives within a regulated banking environment.
The role focuses on designing and building enterprise-grade in-house frameworks, supporting high-volume batch and CDC-based incremental processing using Cloudera platform, and enabling ongoing Google Cloud Platform (GCP) modernization efforts.
Technology & Skill Requirements
• Apache Spark (PySpark and/or Scala) in large-scale production environments
• Cloudera Hadoop ecosystem (HDFS, Hive, YARN, Spark on Cloudera)
• Strong SQL expertise with complex transformations, performance tuning, and reconciliation logic
• Enterprise RDBMS experience with Oracle and MS SQL Server
• Batch ingestion, incremental ingestion, and CDC processing patterns
• CDC concepts and tooling (tool-agnostic: GoldenGate, Debezium, or equivalent)
• Data merge, deduplication, watermarking, checkpointing, and SCD handling
• Google Cloud Platform services including Dataproc , Composer and Dataplex
• Hybrid on prem to cloud data architecture and migration patterns
• Metadata-driven framework development and data quality validation techniques
• CI/CD pipeline implementation using enterprise tooling (GitHub Actions, Jenkins, DevOps)
• Git-based development workflows, code reviews, and automated testing practices
• Experience using Copilot or similar AI-assisted development tools safely and effectively in enterprise environments
• Logging, monitoring, alerting, and operational readiness practices
• Secure coding, access control, and compliance-aware development
• Documentation of design artifacts, runbooks, and operational procedures






