AWS Data Engineer - Hadoop, Spark & Kafka

Job Title: AWS Data Engineer Hadoop Spark & Kafka
Work Location: Maryland Heights MO 63043 - Hybrid
Vendor Rate: $50/hr
Contract duration: 12 Months
Interview Process (Is face to face required): Yes

Must Have skills:
AWS Hadoop

Detailed Job Description
Key Responsibilities
Design build and Eligible to workimize scalable batch and real-time data pipelines using Apache Spark (Scala/Python) Core Java and Apache Kafka to process high-volume data.
Manage and maintain enterprise data Lakehouse architectures spanning AWS and Cloudera environments leveraging S3 Apache Iceberg and Hive for scalable storage and querying.
Implement Change Data Capture (CDC) and write complex SQL to integrate data from relational databases (Oracle SQL Server) into dimensional data warehouses.
Automate and orchestrate pipeline workflows using Unix shell scripting and Python.
Lead and support migration of legacy Hadoop workloads to AWS cloud-native architectures.
Monitor troubleshoot and tune JVM and Spark job performance to ensure reliability and efficiency at scale.
Ensure all data pipelines and storage practices adhere to regulatory compliance and data governance standards.
Collaborate with cross-functional teams (data architects analysts platform engineers) to translate business requirements into robust data solutions.

Required Skills & Technology:
Strong programming experience in Scala/Python (Spark) and Core Java
Hands-on experience with Apache Kafka for streaming data pipelines
Working knowledge of AWS services (S3) and Cloudera platform tools (Hive Iceberg)
Strong SQL skills including CDC concepts across Oracle and SQL Server
Experience with dimensional data warehouse modeling
Proficiency in Unix shell scripting and Python for automation
Experience migrating on-prem Hadoop workloads to cloud platforms
Understanding of JVM internals and Spark performance tuning techniques

Preferred Qualifications:
Prior experience in the Communications/Telecom domain (CDRs network telemetry data)
Familiarity with data governance and regulatory compliance frameworks
Bachelors degree in computer science Engineering or a related field or equivalent practical experience

Minimum years of experience: 8-10 years

Certifications Needed :No

Top 3 responsibilities you would expect the Subcon to shoulder and execute
Manage and maintain enterprise data lake house architectures spanning AWS and Cloudera environments leveraging S3 Apache Iceberg and Hive for scalable storage and querying. Implement Change Data Capture CDC and write complex SQL to integrate data from relational databases Oracle SQL Server into dimensional data warehouses.
Automate and orchestrate pipeline workflows using Unix shell scripting and Python. Lead and support migration of legacy Hadoop workloads to AWS cloud native architectures.

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Required Experience:

IC