Sr. Data Platform Engineer

eTeam

Washington (District of Columbia)

On-site

USD 89,544 - 96,432

Full time

14 days+

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Job summary

A recruitment agency is looking for a Sr. Data Platform Engineer in Washington, DC. The role requires extensive experience in data engineering, focusing on real-time streaming and cloud-native architectures. Ideal candidates should have solid knowledge of Apache Kafka, data governance, and a strong grasp of distributed systems. This contract position offers competitive hourly pay and the opportunity to work with cutting-edge technology.

Qualifications

6+ years of experience in data engineering, real-time streaming, or event-driven architectures.
Strong hands-on expertise in Amazon MSK and Kafka Streams.
Deep understanding of distributed systems and event-driven microservices.

Responsibilities

Manage data flows with Apache NiFi and workflow orchestration with Apache Airflow.
Ensure compliance with data governance and security best practices.
Expertise in cloud-native data infrastructure and container orchestration.

Skills

Data engineering

Amazon MSK

Apache NiFi

Kafka Streams

AWS/GCP/Azure

Kubernetes

Data governance

Job description

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This range is provided by eTeam. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$75.00/hr - $80.00/hr

Direct message the job poster from eTeam

Service Delivery Specialist @ eTeam || Business Professional Recruitment || Pharma Recruitment || Medical Device Recruitment || Ex- Global Technical…

Job Title: Sr. Data Platform Engineer

Location: Washington, DC, 20001

Duration: 17 months

Pay Range: $(65.00 - 70.00)/hr on W2 all-inclusive without benefits

Job Description:

6+ years of experience in data engineering, real-time streaming, or event-driven architectures.
Strong hands-on expertise in Amazon MSK (Managed Streaming for Apache Kafka), Kafka Streams, and Kafka Connect.
Experience in managing data flows with Apache NiFi and workflow orchestration with Apache Airflow.
Proficiency in managing MQ and other Pub/Sub messaging platforms and frameworks.
Experience with Flink, Spark Streaming, or similar frameworks for real-time processing.
Deep understanding of distributed systems, stream processing semantics, and event-driven microservices.
Expertise in cloud-native data infrastructure (AWS/GCP/Azure), Kubernetes, and container orchestration.
Strong grasp of data governance, schema evolution, security, and compliance best practices.

Seniority level