qode.world

AWS Solution Architect

qode.world

full-time

Posted on:

Location Type: Hybrid

Location: San Francisco • California • United States

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Tech Stack

AirflowApacheAWSCloudDynamoDBHadoopHBaseHDFSKafkaPySparkPythonScalaSparkSQL

About the role

  • 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.

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
  • 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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
Solution architectureData ingestionData preparationData transformationBig Data technologiesPythonScalaHadoopSQLData processing
Soft skills
Analytical skillsProblem-solving skillsOrganizational skillsCommunication skillsInterpersonal skillsTeamworkAutonomy