DATA ENGINEER__ NYC / Washington DC// Fulltime Only

Overview

Full Time

Skills

Data Architect
aws
Airflow
DBT

Job Details

Hi,

Hope you are doing well!

Please have a look below JD & if you are interested then confirm your best Annual Salary.

Position- : Data Engineer

Location NYC / Washington DC

Hybrid 3 Days a week

Mandate Skills: DBT+ Airflow + AWS

Please look for candidates with 15yrs + of experience as Architect & Development experience. There are 2 Mandatory Combinations Highlighted please read the email carefully till bottom line.

Position Summary

We're looking for a data engineer to build and maintain ELT pipelines using Apache Airflow, dbt, 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.
  • Hands-on with dbt for modular, version-controlled data transformations.
  • 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.

Primary Skills:

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

DBT Proficiency: model development:

  • Experience in creating complex DBT models including incremental models, snapshots and documentation. Ability to write and maintain DBT macros for reusable code

Testing and documentation:

  • Proficiency in implementing DBT tests for data validation and quality checks
  • Familiarity with generating and maintaining documentation using DBT's built in features

Version control:

  • Experience in managing DBT projects using git ,including implementing CI/CD process from the scratch

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
  • Experience in creating custom DBT macros using jinja and Python allowing for reusable components within dbt models
  • 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

Ravi Kumar

Desk: |Cell-

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.