Data Engineer (Dallas) at Robert Half

We are seeking a highly experienced Senior Data Engineer with deep expertise in modern data engineering frameworks and cloud-native architectures, primarily on AWS. This role focuses on designing, building, and optimizing scalable data pipelines and distributed systems.You will collaborate cross-functionally to deliver secure, high-quality data solutions that drive business decisions.Key ResponsibilitiesDesign & Build: Develop and maintain scalable, highly available AWS-based data pipelines, specializing in EKS/ECS containerized workloads and services like Glue, EMR, and Lake Formation.Orchestration: Implement automated data ingestion, transformation, and workflow orchestration using Airflow, NiFi, and AWS Step Functions.Real-time: Architect and implement real-time streaming solutions with Kafka, MSK, and Flink.Data Lake & Storage: Architect secure S3 data storage and govern data lakes using Lake Formation and Glue Data Catalog.Optimization: Optimize distributed processing solutions (Databricks, Spark, Hadoop) and troubleshoot performance across cloud-native systems.Governance: Ensure robust data quality, security, and governance via IAM, Lake Formation controls, and automated validations.Mentorship: Mentor junior team members and foster technical excellence.RequirementsExperience: 7+ years in data engineering; strong hands-on experience designing cloud data pipelines.AWS Expertise: Deep proficiency in EKS, ECS, S3, Lake Formation, Glue, EMR, IAM, and MSK.Core Tools: Strong experience with Kafka, Airflow, NiFi, Databricks, Spark, Hadoop, and Flink.Coding: Proficiency in Python, Scala, or Java for building data pipelines and automation.Databases: Strong SQL skills and experience with relational/NoSQL databases (e.g., Redshift, DynamoDB).Cloud-Native Skills: Strong knowledge of Kubernetes, containerization, and CI/CD pipelines.Education: Bachelors degree in Computer Science or related field.