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# Lead Data Engineer

- **Company:** OpenKyber LLC
- **Location:** Plano, TX, United States
- **Experience:** Expert
- **Contract:** Temporary to permanent
- **Skills:** Java (Programming Language), Amazon Web Services, Microsoft Azure, Batch Processing, Big Data, Cloud Computing, Cloud Database, Information Engineering, Data Governance, Data Infrastructure, Data Systems, Database Queries, Distributed Data Store, Apache Hadoop, Python (Programming Language), Key Management, DataOps, Scaled Agile Framework, SQL Databases, Google Cloud, Data Ingestion, Apache Spark, Electronic Medical Records, Low Latency, Apache Kafka, Video Streaming, Data Delivery, Data Pipelines
- **Published:** October 11, 2026
- **Apply:** https://www.careerjet.com/jobad/us2d4cab7a739f55ea8dcad6d85acc2f1c

## About the Role

Location : Plano, TX (ONLY), Capital One Formers only On-site/Hybrid/Remote : Hybrid If Hybrid, what days in office : On-site three days per week in Plano. Tuesday, Wednesday and Thursday on-site. Duration : 7-Month Contract Current Project : This is a migration project focused on placing candidates in the appropriate roles based on their technical background and skill set. The ideal candidate will have a strong Data Engineering background with extensive experience working with Big Data technologies . Day-to-Day Responsibilities: Engineers will operate within a standard engineering environment, following established development practices, processes, and reporting standards. The hiring team is particularly interested in candidates with the following experience: Strong experience with Big Data technologies and large-scale data environments. Proficiency in Python is preferred, along with experience in Java . Candidates who are highly skilled in one primary programming language should
also have working knowledge of the other. Strong SQL skills and experience working with complex data environments. Hands-on experience with AWS and cloud technologies , including cloud-based data solutions and services. Experience designing, developing, and supporting data pipelines and data orchestration workflows . A strong Data Engineering background , with experience building and supporting scalable data solutions. Experience working in an Agile engineering environment and collaborating effectively with cross-functional teams. Hands-on experience with Kafka and event-streaming technologies. Experience with Spark for large-scale batch processing and distributed data workloads. Given the pace and immediate needs of the migration project, candidates with prior Capital One experience will be better positioned to hit the ground running with minimal ramp-up time and quickly understand the organization's environment, processes, and technical landscape. Interview Process : One round within
1-Hour. Will be asking questions about previous Capone experience. Technical Assessments Required : Technical Questions with Coding questions. Key Responsibilities Design, build, and operate large-scale batch and real-time data pipelines that move, transform, and publish data across the enterprise with high reliability and low latency. Collaborate with Agile engineering teams to architect and implement end-to-end data solutions, from data ingestion and workflow orchestration through event streaming and downstream data delivery. Required Qualifications 4%2B years of experience building or operating data pipelines and orchestration systems. 4%2B years of data or application engineering experience with Java, Python, and SQL . 4%2B years of experience building and operating real-time or event-driven data systems. 4%2B years of experience working with distributed data and computing technologies such as Kafka, Spark, EMR, Hadoop, or equivalent platforms . 4%2B years of experience with
cloud-based data warehousing platforms at scale. 4%2B years of experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform . 3%2B years of experience with pipeline scheduling and workflow orchestration tools. 2%2B years of experience implementing secure secrets management and credential handling in production environments. 2%2B years of experience working in Agile engineering environments. Familiarity with data observability practices, including monitoring, alerting, SLA tracking, and data quality frameworks . Experience working in financial services or other regulated, compliance-driven industries .
For applications and inquiries, contact:hirings@openkyber.com