AWS Data & Solution Engineer

Acunor Infotech

New York, NY, United States

6 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Amazon Web Services Amazon S3 Data Analysis Apache HTTP Server Unit Testing Code Review Codecs Extract Transform Load (ETL) Data Security Relational Databases Software Debugging File Systems

+44 more

Amazon DynamoDB Apache Hadoop Hadoop Distributed File System JSON Python (Programming Language) MongoDB NoSQL OAuth Oracle (Applications) Swagger Software Deployment Systems Integration Web Services Extensible Markup Language (XML) Enterprise Data Management Parquet Datadog Freeform SQL Flask (Web Framework) Snowflake Apache Spark Boto3 Electronic Medical Records AWS Lambda Fastapi Pandas Build Management Data Lakes Pyspark Information Technology Avro AWS Glue Data Analytics AWS Data Analytics Apache Kafka Virtual Agents Cloudwatch Restful APIs GPT Data Pipelines Docker Confluent Amazon Redshift Oracledb

Job description

We are looking for an Sr AWS Data & Solutions Engineer with primary skills on Python & PySpark development who will be able to design and build solutions for one of our Fortune 500 Client programs, which aims towards building an Enterprise Data Lake on AWS Cloud platform, build Data pipelines by developing several AWS Data Integration, Engineering & Analytics resources. You will be responsible for building API services using FastAPI or Flask frameworks. Key Responsibilities

Design, build and unit test applications on Spark framework on Python.
Build Python and PySpark based applications based on data in both Relational databases (e.g. Oracle), NoSQL databases (e.g. DynamoDB, MongoDB) and filesystems (e.g. S3, HDFS)
Build AWS Lambda functions on Python runtime leveraging awswrangler, pandas, json, requests
Build PySpark based data pipeline jobs on AWS Glue ETL or EMR Clusters
Build Python based event-driven integration with Kafka Topics, leveraging Confluent libs
Leveraged Apache Iceberg to manage schema evolution and ACID-compliant CDC merges within the data lake
Design and Build API services using FastAPI, understand the swagger metadata files and implement OAuth2/JWT authentication for protected endpoints
Build the process orchestration pipelines using AWS Step Functions and Eventbridge rules.
Optimize performance for data access requirements by choosing the appropriate native Hadoop file formats (Avro, Parquet, ORC etc) and compression codec respectively.
Deploy applications on Docker and Kubernetes containers
Leverage copilot/GPT for agentic coding of above tech stack
Optimize performance of Spark applications in Hadoop using configurations around Spark Context, Spark-SQL, Data Frame, and Pair RDD’s
Setup the Glue crawlers to catalog OracleDB tables, MongoDB collections and S3 objects
Ability to monitor, troubleshoot and debug failures using AWS CloudWatch and Datadog
Ability to solve complex data-driven scenarios and triage towards defects and production issues
Participate in code release and production deployment.
Create documentation for user adoption, deployments, runbook, and support client users for enablement or for any issues encountered.
Perform code reviews with the team and enable them to develop code for complex scenarios
Participate in the agile development process, and document and communicate issues and bugs relative to data standards in scrum meetings
Work collaboratively with onsite and offshore team.
Voice the opinions to multiple teams and thus driving the entire initiative with strong leadership

Requirements

Bachelor’s Degree or equivalent in computer science or related and minimum 10+ years of experience
Certified on one of - Solution Architect, Data Engineer or Data Analytics Specialty by AWS
Require hand-on experience on Python and PySpark programming
Require hands-on experience on AWS S3, Glue ETL & Catalog, Lamba Functions, EventBridge, Step Functions, Athena
Require hands-on experience on Kafka integrations
Require hands-on experience working on different file formats i.e. avro, parquet, orc, json, xml
Require hands-on experience on Python pandas, requests, boto3 module
Require hands-on experience in writing complex SQL queries
Require hands-on experience using REST APIs using FastAPI or Flask
Require hands-on experience building Agentic AI workflows
Preferred expertise on Snowflake, AWS Redshift & DynamoDB
Ability to use AWS services, predict application issues and design proactive resolutions
Require Technical Coordination skills to drive requirements and technical design
Requires aptitude to help build skillset within organization

Knowledge, Skills & Abilities

Data pipelines using Python and PySpark on AWS Glue, EMR and lambda functions.
Develop and secure RESTful APIs (FastAPI) on Docker/EKS containers and implement OAuth2/JWT authentication for protected endpoints
Hands-on experience with Apache Iceberg tables for cdc and latest snapshots
Event based pipelines for consuming/publishing to/from Apache Kafka/MSK
Lead and communicate complex technical designs and leverage copilot/GPT for agentic coding of above tech stack