Raas Infotek LLC
Senior Data Engineer
Plano, Texas, USA · Senior · Contract
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About the role
- Ensure data quality, governance, security, and compliance standards are met.
- Mentor junior engineers and provide technical leadership to the data engineering team.
Responsibilities
- Design and implement scalable, high-performance data pipelines and ETL/ELT processes.
- Develop and maintain enterprise data lakes, data warehouses, and data marts.
- Lead data architecture initiatives and establish best practices for data engineering.
- Optimize data storage, processing, and retrieval for large-scale datasets.
- Collaborate with Data Scientists, Business Analysts, and stakeholders to deliver data solutions.
- Drive cloud migration and modernization initiatives.
Requirements
- 10+ years of experience in Data Engineering or related roles.
- Strong expertise in Python, SQL, and PySpark.
- Hands-on experience with Apache Spark, Kafka, and data streaming technologies.
- Experience with cloud platforms: AWS, Azure, or Google Cloud Platform.
- The ideal candidate will have extensive experience in cloud-based data solutions, data warehousing, big data technologies, and data architecture.
- Required Skills 10+ years of experience in Data Engineering or related roles.
Nice to have
- Bachelor''s or Master''s degree in Computer Science, Engineering, or related field.
- Cloud certifications (AWS, Azure, or Google Cloud Platform) preferred.
- Experience leading data engineering teams and large-scale data projects.
- Key Technologies Python | SQL | PySpark | Spark | Kafka | Airflow | dbt | Snowflake | AWS/Azure/Google Cloud Platform | Data Warehousing | ETL/ELT | Terraform | CI/CD
- AWS, Azure, or Google Cloud Platform.
- Strong knowledge of data warehousing solutions such as Snowflake, Redshift, or BigQuery.
- Experience with ETL/ELT tools such as Airflow, Informatica, or dbt.
- Deep understanding of data modeling, performance tuning, and data governance.
This listing is sourced directly from Raas Infotek LLC's careers page and normalized into a canonical job model.