Senior Technical Lead

HCL Tech•Seattle, WA

1d•Remote

About The Position

Develop Services to enable data ingestion from and synchronization with systems which expose required data access mechanisms ensuring near-real-time updates. Ingest data from multiple sources using Python and any other ETL tools. Design and implement an event-driven architecture using AWS EventBridge, Kafka, or SNS/SQS for real-time data streaming. Design, implement, and maintain scalable data pipelines that integrate both on-prem and AWS cloud environments. Develop efficient Python scripts and applications using libraries like pandas, NumPy, etc., to handle and process large datasets. Work with various NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB) to support high-performance data storage and retrieval. Develop and deploy applications in a cloud-native architecture, leveraging modern cloud technologies for scalability and resilience. Continuously monitor data workflows and systems, troubleshoot issues, and optimize performance for reliability and scalability. Transition existing pipeline to MSSQL server. Collaborate with the business application owner on the existing data architecture, including data ingestion, data pipelines, business logic, data consumption patterns, and analytics requirements. Design and document the target data architecture, pipelines, processing and analytics architecture. Identify opportunities for optimization and consolidation. Collaboration with the data team on decomposition of business logic and data transformation patterns.

Requirements

AWS Glue
Kafka, or SNS/SQS
Python / PySpark
Data lake
Cloudwatch
Cloudtrail
SNS/SQS
DB design and SQL
AWS IAM
EKS

Responsibilities

Develop Services to enable data ingestion from and synchronization with system which exposes required data access mechanisms ensuring near-real-time updates
Ingest data from multiple sources using the python and any other ETL tools
Design and implement an event-driven architecture using AWS EventBridge, Kafka, or SNS/SQS for real-time data streaming
Design, implement, and maintain scalable data pipelines that integrate both on-prem and AWS cloud environments.
Develop efficient Python scripts and applications using libraries like pandas, NumPy, etc., to handle and process large datasets.
Work with various NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB) to support high-performance data storage and retrieval.
Develop and deploy applications in a cloud-native architecture, leveraging modern cloud technologies for scalability and resilience.
Continuously monitor data workflows and systems, troubleshoot issues, and optimize performance for reliability and scalability
Transition existing pipeline to MSSQL server
Collaborate with the business application owner on the existing data architecture, including data ingestion, data pipelines, business logic, data consumption patterns, and analytics requirements
Design and document the target data architecture, pipelines, processing and analytics architecture
Identify opportunities for optimization and consolidation
Collaboration with data team on decomposition of business logic and data transformation patterns