Location - Dallas, TX,Jacksonville, FL, Tampa, FL, and Jersey City, NJ
Role- AWS Data Engineer
Duration: Full Time (Permanent)
Roles & Responsibilities
Job Description:
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
ABOUT US
Apptad offers strategic consulting, enterprise information management and digital transformation services. With globally connected offices in US and India along with a team of trained and certified IT resources, Apptad ensures quick and effective delivery to its customers.Apptad is relentlessly reinventing the outlook of how companies leverage data.
With an effort to enable our customers the ability to solve biggest problems within their organization.We perceive our clients problems and respond with custom solutions instead of handing over boilerplate responses.
OUR MISSION
Customer Focus: We listen carefully to the needs of our clients so that we know what s important for their business and can design a customized solution for their business.
Innovation: As a firm, we believe in constantly upgrading ourselves and improving our solutions to adapt to the changing landscape of technology.
Accountability and Ethics: We believe in taking our commitments as seriously as our customers and living up to them while building trust for a long term business relationship.
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