Apply for this opportunity

This job application is on an outside website. Be sure to review the job posting there to verify it's the same.

Apply Offsite

Senior Data Engineer

Job

Lorven Technologies Inc.

Irving, TX (In Person)

Full-Time

Posted 6 days ago (Updated 1 day ago) • Actively hiring

Expires 7/4/2026

See Job Scorecard

Review key factors to help you decide if the role fits your goals.

How is this calculated?

Pay Growth

out of 5

Not enough data

Not enough info to score pay or growth

Job Security

out of 5

Not enough data

Calculating job security score...

Total Score

out of 100

Average of individual scores

Were these scores useful?

Skill Insights

Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.

Job Description

Senior Data Engineer at Lorven Technologies Inc. Senior Data Engineer at Lorven Technologies Inc. in Irving, Texas Posted in 2 days ago.

Type:

full-time

Job Description:

HI Our client is looking for a Senior Data Engineer in Irving, TX / Wilmington, DE. Below is the detailed requirement.

Title :

Senior Data Engineer Location :

Irving, TX /

Wilmington, DE Required Skills :

Apache Spark (PySpark / Scala), Cloudera Hadoop and CDC Job description: Bachelor's degree in computer science, Information Technology, or a related field 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