Hiring: Data Engineer / Big Data ML Engineer | Plano, TX (100% Onsite) | Capital One
Location: Plano, TX (100% Onsite)
End Client: Capital One Financial Corporation
Employment Type: Contract (09/08/2026 – 03/31/2027)
Our Rate: $65/hr C2C | $61/hr W2
Experience: 8+ Years
We are looking for an experienced Data Engineer / Big Data ML Engineer to build scalable, high-performance data platforms supporting enterprise analytics and Machine Learning initiatives. If you're passionate about Big Data, distributed computing, cloud technologies, and real-time data engineering, we'd love to hear from you!
Key Responsibilities
✅ Design, build, and maintain scalable batch and real-time data pipelines.
✅ Develop distributed data processing solutions using Apache Spark, Kafka, Hadoop, and Amazon EMR.
✅ Build robust ETL/ELT frameworks for enterprise-scale data processing.
✅ Design cloud-native data solutions on AWS, Azure, or GCP.
✅ Develop data engineering solutions using Java, Python, and SQL.
✅ Implement event-driven architectures and real-time data processing.
✅ Build workflow orchestration solutions using Airflow, AWS Step Functions, Azure Data Factory, or Prefect.
✅ Optimize pipeline performance, scalability, monitoring, and data quality.
✅ Collaborate with Data Scientists, ML Engineers, DevOps, and Product Teams.
✅ Support production environments, troubleshoot pipeline issues, and drive continuous improvements.
Required Skills
✔️ 8+ years of Data Engineering / Big Data experience.
✔️ Strong expertise in Java, Python, and SQL.
✔️ Hands-on experience with Apache Spark, Apache Kafka, Hadoop, and Amazon EMR.
✔️ Strong knowledge of ETL/ELT, Data Pipelines, and Distributed Computing.
✔️ Experience building Real-Time Data Processing and Event-Driven Architectures.
✔️ Experience with AWS, Azure, or Google Cloud Platform (GCP).
✔️ Knowledge of Snowflake, Redshift, BigQuery, Azure Synapse, or similar cloud data warehouses.
✔️ Experience with Agile, Git, CI/CD, and DevOps collaboration.
⭐ Preferred Skills
✅ Machine Learning data pipelines & Feature Engineering.
✅ Airflow, Prefect, AWS Step Functions, or Azure Data Factory.
✅ Data Lake / Lakehouse technologies (Delta Lake, Apache Iceberg, Apache Hudi).
✅ Data Quality Frameworks and Monitoring/Observability tools.
✅ Financial Services or other regulated industry experience.
Interested candidates, please share your updated resume