Data Engineer

  • Washington, NC
  • Posted 7 hours ago | Updated 7 hours ago

Overview

On Site
$100,000 - $180,000
Full Time

Skills

Amazon Lambda
Amazon Redshift
Amazon S3
Amazon Web Services
Apache Airflow
Cloud Computing
Customer Facing
Data Analysis
Data Engineering
Data Modeling
Data Processing
Data Quality
Data Storage
Data Warehouse
ELT
Electronic Health Record (EHR)
Python
Snow Flake Schema
React.js
RESTful

Job Details

Mandate Skills: AWS + Python + Airflow

Position Summary:

We re looking for a data engineer to build and maintain ELT pipelines using Apache Airflow, and Snowflake in an AWS cloud environment. Should have experience in modular python coding with experience in deploying any container-based services in aws with monitoring setup as well.

Key Skills & Experience:

  • Strong SQL and Snowflake expertise, including performance tuning and data modeling.
  • Proficient in Python for scripting, automation, and working with REST APIs.
  • Experience with Apache Airflow for orchestration and workflow monitoring.
  • Solid experience with AWS services (e.g., S3, Lambda, IAM, CloudWatch) in data engineering workflows.
  • Experience integrating and processing data from REST APIs.
  • Understanding of data quality, governance, and cloud-native troubleshooting.

Role Responsibilities:

Primary Skillset :(Must have)

10+ Years Experience Great Communicator/Client Facing Individual Contributor 100% Hands on in the mentioned skills

AWS Expertise:

Data STORAGE solutions: In depth understanding of AWS S3 for data storage, including best practices for organization and security

Experience with AWS redshift for data warehousing and performance optimization

Data Integration:

Familiarity with Aws glue for ETL processes and orchestration -Nice to have

Experience with AWS lambda for serverless data processing tasks

Workflow Orchestration:

Proficiency in using Apache Airflow on AWS to design ,schedule and monitor complex data flows

Ability to integrate Airflow with AWS services and DBT models such as triggering a DBT model or EMR or reading from s3 writing to redshift

Data Lakes and Data warehousing:

Understanding the architecture of data lakes vs data warehouses and when to use each

Experience with amazon Athena for querying data directly in s3 using SQL

Monitoring and Logging:

Familiarity with AWS cloud watch for monitoring the pipelines and setting up alerts for workflow failures

Cloud Security:

Knowledge of AWS security best practices ,including IAM roles, encryption, DBT profiles access configurations

Programming Skills:

Python:

Proficiency in Pandas and NumPy for data analysis and manipulation

Ability to write scripts for automating ETL processes and scheduling jobs using airflow

Knowledge on how to implement conditional logic in DBT through python

SQL:

Advanced SQL skills, including complex joins ,window functions, CTE's and subqueries

Experience in optimizing SQL queries for performance and optimization

Secondary Skill Set/Preferred :( Good to have)

React/streamlit, SQL, Snowflake, AWS cloud,REST API via FastAPI or similar

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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