AWS Data Engineer (AWS certification) Texas 75023 FulltimeFTE only

NO C2C OR C2H - ONLY FULLTIME

IN-PERSON Interview this Week in any of the below Locations

Role - AWS Data Engineer

Location - Irving/Dallas/Plano TX - 75234 / 75038 / 75023

Fulltime/FTE

We are seeking a highly skilled and motivated AWS Certified Engineer to design build and optimize scalable data solutions within the Amazon Web Services (AWS) ecosystem. The ideal candidate will have strong expertise in big data processing using PySpark and a deep understanding of data warehousing concepts including Hive and modern table formats like Iceberg. This role involves developing deploying and managing robust efficient and secure data pipelines and analytics solutions on AWS leveraging core networking and compute services.

Responsibilities:

AWS Solution Design & Implementation: Design develop and deploy scalable and cost-effective data solutions on AWS leveraging services such as S3 (for data lakes) EC2 EMR Glue Athena Lambda Redshift and Kinesis.

Data Pipeline Development: Build and maintain robust ETL/ELT data pipelines using PySpark for data ingestion transformation and loading into various data stores including those utilizing open table formats like Iceberg.

Big Data Processing: Develop and optimize big data processing jobs using PySpark on AWS EMR or AWS Glue handling large datasets efficiently and integrating with Iceberg table formats.

Data Warehousing: Design implement and manage data warehousing solutions including schema design data modeling and query optimization with a focus on Hive and modern data lake table formats like Iceberg for historical data and analytical queries.

Cloud Infrastructure & Networking: Implement secure and robust cloud infrastructure components including VPCs subnets routing and security groups to ensure proper connectivity and isolation for data solutions.

Containerized Workloads: Design deploy and manage containerized data processing applications on Amazon Elastic Kubernetes Service (EKS).

Performance Tuning & Optimization: Optimize AWS resources and big data applications (Spark Hive Iceberg) for performance cost and efficiency.

Data Governance & Security: Implement best practices for data security access control and compliance within AWS including IAM policies S3 bucket policies and encryption.

Monitoring & Troubleshooting: Set up monitoring alerting and logging for data pipelines and AWS infrastructure; troubleshoot and resolve issues promptly.

Automation: Develop and maintain automation scripts using Python and shell scripting for infrastructure provisioning deployment and operational tasks.

Collaboration: Work closely with data scientists analysts and other engineering teams to understand data requirements and deliver reliable data solutions.

Qualifications :

AWS Certification: Hold at least one AWS certification (e.g. AWS Certified Solutions Architect Associate AWS Certified Data Analytics Specialty AWS Certified Developer Associate).

AWS Services Expertise: Hands-on experience with key AWS services for data processing and storage including:

Storage: S3 (for data lakes) EC2

Data Processing: EMR Glue Athena Lambda

Networking: VPC Subnets Routing Security Groups

Containerization: EKS

Big Data Processing: Strong proficiency in PySpark for developing complex data transformations and analytics.

Data Lake Table Formats: Practical experience with Apache Iceberg for managing and querying data lakes.

Data Warehousing: In-depth knowledge and practical experience with Apache Hive for data storage querying and schema management.

Programming Languages:

Python: Expert-level proficiency in Python for scripting data manipulation and AWS automation (Boto3).

Shell Scripting: Proficient in shell scripting for automation and operational tasks.

Database & SQL: Strong SQL skills for data querying and manipulation.

Data Concepts: Solid understanding of ETL/ELT processes data modeling distributed computing and data governance.

Good to Have Skills

Containerization Orchestration: Experience with Kubernetes for deploying and managing containerized applications.

CI/CD: Experience with CI/CD tools and practices (e.g. AWS CodePipeline GitHub Actions GitLab CI) for automating deployment of data solutions.

Orchestration: Experience with workflow orchestration tools like Apache Airflow.

Version Control: Proficient in using Git for source code management.

Other Big Data Technologies: Exposure to other big data technologies like Apache Kafka Flink or Presto.

Certifications

AWS Certified Solutions Architect Associate/Professional

AWS Certified Data Analytics Specialty

AWS Certified Developer Associate

Thanks & Regards

Romit Karn
Work#:

Mailto:

Synchrony Systems Inc.

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