AWS Solution Architect

Qode • California City, CA

4h

About The Position

Role: AWS Solution ArchitectLocation: San Francisco, CA Job Purpose: Designing Solution architecture, and work on Data Ingestion, Preparation, and Transformation. Debugging the production failures and identifying the solution. Developing efficient frameworks for development and testing using (AWS Dynamo DB, EKS, Kafka, Kinesis/Spark/Streaming/Python, etc.) to enable a seamless data ingestion process onto the AWS cloud platform. Enabling Data Governance and Data Discovery Platform Building data processing framework using Spark, Databricks, and python Exposure to Data Security Framework on the cloud Exposure to Data Pipeline Automation using DevOps tools Exposure to Job Monitoring framework along with validations and automation Exposure to handling structured, Unstructured, and Streaming datasets. Must have - Technical & Soft Skills Solid hands-on and Solution Architecting experience in Big-Data Technologies (AWS preferred) Hands-on experience in: AWS Dynamo DB, EKS, Kafka, Kinesis, Glue PySpark, EMR PySpark Hands-on experience with programming languages like Python, Scala with Spark. Good command and working experience on Hadoop/Map Reduce, HDFS, Hive, HBase, and No-SQL Databases Hands-on working experience on any of the data engineering/analytics platforms (Hortonworks/Cloudera/ MapR/ AWS), AWS preferred Hands-on experience in Data Ingestion Apache Nifi, Apache Airflow, Sqoop, and Ozzie Hands-on working experience in data processing at scale with event-driven systems, message queues (Kinesis/Kafka/Flink/Spark Streaming) Hands-on working Experience with AWS Services like EMR, Kinesis, S3, CloudFormation, Glue, API Gateway, Lake Foundation Hands-on working Experience with AWS Athena Data Warehouse exposure on Apache Nifi, Apache Airflow, Kylo Operationalization of ML models on AWS (e.g. deployment, scheduling, model monitoring etc.) Feature Engineering/Data Processing to be used for Model development Experience gathering and processing raw data at scale (including, writing scripts, web scraping, calling APIs, writing SQL queries, etc.) Experience building data pipelines for structured/unstructured, real-time/batch, events/synchronous/ asynchronous using MQ, Kafka, Steam processing Hands-on working experience in analyzing source system data and data flows, working with structured and unstructured data Must be very strong in writing SQL queries Strengthen the Data engineering team with Big Data solutions Strong technical, analytical, and problem-solving skills Strong organizational skills, with the ability to work autonomously as well as in a team-based environment Pleasant Personality, Strong Communication & Interpersonal Skills

Requirements

• Solid hands-on and Solution Architecting experience in Big-Data Technologies (AWS preferred)
• Hands-on experience in: AWS Dynamo DB, EKS, Kafka, Kinesis, Glue PySpark, EMR PySpark
• Hands-on experience with programming languages like Python, Scala with Spark.
• Good command and working experience on Hadoop/Map Reduce, HDFS, Hive, HBase, and No-SQL Databases
• Hands-on working experience on any of the data engineering/analytics platforms (Hortonworks/Cloudera/ MapR/ AWS), AWS preferred
• Hands-on experience in Data Ingestion Apache Nifi, Apache Airflow, Sqoop, and Ozzie
• Hands-on working experience in data processing at scale with event-driven systems, message queues (Kinesis/Kafka/Flink/Spark Streaming)
• Hands-on working Experience with AWS Services like EMR, Kinesis, S3, CloudFormation, Glue, API Gateway, Lake Foundation
• Hands-on working Experience with AWS Athena
• Data Warehouse exposure on Apache Nifi, Apache Airflow, Kylo
• Operationalization of ML models on AWS (e.g. deployment, scheduling, model monitoring etc.)
• Feature Engineering/Data Processing to be used for Model development
• Experience gathering and processing raw data at scale (including, writing scripts, web scraping, calling APIs, writing SQL queries, etc.)
• Experience building data pipelines for structured/unstructured, real-time/batch, events/synchronous/ asynchronous using MQ, Kafka, Steam processing
• Hands-on working experience in analyzing source system data and data flows, working with structured and unstructured data
• Must be very strong in writing SQL queries
• Strong technical, analytical, and problem-solving skills
• Strong organizational skills, with the ability to work autonomously as well as in a team-based environment
• Pleasant Personality, Strong Communication & Interpersonal Skills

Nice To Haves

• Scripting: Unix or Shell scripting
• Exposure to various ETL and Business Intelligence tools
• Experience in data warehouse design and best practices
• A strong background in troubleshooting and technology support will be beneficial.

Responsibilities

• Designing Solution architecture
• Work on Data Ingestion, Preparation, and Transformation
• Debugging the production failures and identifying the solution
• Developing efficient frameworks for development and testing using (AWS Dynamo DB, EKS, Kafka, Kinesis/Spark/Streaming/Python, etc.) to enable a seamless data ingestion process onto the AWS cloud platform
• Enabling Data Governance and Data Discovery Platform
• Building data processing framework using Spark, Databricks, and python
• Strengthen the Data engineering team with Big Data solutions

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 11-50 employees