Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Washington, DC, United States
Posted
19 hours ago
DockerSQLScalaAWSETLMachine LearningApacheDatabricksKafkaKubernetesPythonStakeholder ManagementTerraform
Job Description
Key Responsibilities
- Design end-to-end cloud-native data architectures using AWS and Databricks.
- Architect scalable batch and real-time data processing solutions using Apache Kafka and streaming technologies.
- Lead the design and implementation of enterprise data engineering pipelines and data platforms.
- Define architecture standards, best practices, and governance for data integration and analytics solutions.
- Collaborate with business stakeholders to translate business requirements into scalable technical solutions.
- Provide technical leadership and architectural guidance to development teams throughout the SDLC.
- Optimize data pipelines for performance, scalability, security, and cost efficiency.
- Design data models and integration strategies for structured and semi-structured data.
- Ensure solutions adhere to enterprise security, compliance, and reliability standards.
- Evaluate emerging technologies and recommend innovative solutions to improve business capabilities.
- Support cloud migration and modernization initiatives.
- Mentor engineers and conduct architecture and design reviews.
Required Qualifications
- 8+ years of experience in software, data engineering, or solution architecture.
- Strong experience designing enterprise data platforms on AWS.
- Hands-on expertise with Databricks and the Lakehouse architecture.
- Experience implementing Apache Kafka for real-time event streaming.
- Strong background in Data Engineering, including ETL/ELT pipeline development.
- Experience building scalable real-time and streaming data processing solutions.
- Strong understanding of distributed systems and cloud architecture principles.
- Experience with SQL, Python, or Scala.
- Knowledge of CI/CD, Infrastructure as Code, and cloud-native development practices.
- Excellent communication and stakeholder management skills.
- Databricks Certified Data Engineer Professional
Preferred Qualifications
- Experience with AI/ML platforms or deploying machine learning solutions into production.
- Experience with Delta Lake, Spark Structured Streaming, or similar technologies.
- AWS Certification (Solutions Architect or Data Analytics) is preferred.
- Experience with Terraform, Kubernetes, or Docker is a plus.
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