
Data Scientist and Big Data Expert
1 day ago
We are seeking a skilled professional with expertise in designing, architecting, and implementing data engineering solutions. The ideal candidate will bring hands-on experience in Big Data technologies and AWS Cloud Services.
Key Responsibilities:
- Data Engineering: Design, develop, and optimize Big Data architectures leveraging AWS services for large-scale, complex data processing.
- Data Pipelines: Build and maintain data pipelines using Spark (Scala) for both structured and unstructured datasets.
- Platform Architecture: Architect and operationalize data engineering and analytics platforms (AWS preferred; Hortonworks, Cloudera, or MapR experience a plus).
- AWS Services: Implement and manage AWS services including EMR, Glue, Kinesis, DynamoDB, Athena, CloudFormation, API Gateway, and S3.
- Real-Time Streaming: Work on real-time streaming solutions using Kafka and AWS Kinesis.
- ML Model Deployment: Support ML model operationalization on AWS (deployment, scheduling, and monitoring).
- Data Analysis: Analyze source system data and data flows to ensure high-quality, reliable data delivery for business needs.
- SQL Queries: Write highly efficient SQL queries and support data warehouse initiatives using Apache NiFi, Airflow, and Kylo.
- Cross-Functional Teamwork: Collaborate with cross-functional teams to provide technical leadership, mentor team members, and strengthen the data engineering capability.
- Troubleshooting: Troubleshoot and resolve complex technical issues, ensuring scalability, performance, and security of data solutions.
Mandatory Skills & Qualifications:
- Hands-On Experience: Solid hands-on experience in Big Data Technologies (AWS, Scala, Hadoop and Spark Mandatory)
- Proven Expertise: Proven expertise in Spark with Scala
- Experience with AWS Services: Hands-on experience with: AWS services (EMR, Glue, Lambda, S3, CloudFormation, API Gateway, Athena, Lake Formation)
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