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Lead AWS Data Engineer

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Onsite

Lead AWS Data Engineer

Prism IT Global

Lead AWS Data Engineer

Skills

SQL QueriesPythonPostgreSQLSnowflakeAWSdbtPySparkApache Airflow

8 days ago

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Important information


Contract type:

Permanent

Location:

Owings Mills, MD, USA

Work mode:

Onsite

Published on:

12 October 2026

What they need


Must Have Technical/Functional Skills

· 12+ years of solid hands-on experience in Python, AWS Data Services, DBT, Apache Airflow (on Astronomer platform), SQL and PySpark

· Very Good hands-on knowledge on SQL and Data Warehousing life cycle is an absolute requirement.

· Experience in creating data pipelines and orchestrating using DBT & Apache Airflow

· Significant experience with data migrations and development of Operational Data Stores, Enterprise Data Warehouses, Data Lake and Data Marts.

· Experiencing in fixing performance issues / parallelism, Data model exposure is a must.

· Good to have: Experience with cloud ETL and ELT in one of the tools like Glue/EMR or any other ELT tool

· Experience in using Snowflake, DB2, Postgres and other database technologies is plus.

· Excellent communication skills to liaise with Business & IT stakeholders.

· Expertise in planning execution of a project and efforts estimation.

· Exposure to working in Agile ways of working

Roles & Responsibilities

· Lead the design of reliable, secure, and highly available data lakes, data marts and data meshes

· leads the design, development, and maintenance of data integration solutions using Python, AWS Data Services, DBT ensuring data pipeline & data quality

· Collaborate with business stakeholders and architects to define the enterprise data strategy, data models, and migration Roadmap

· Translate complex technical constraints into business insights and manage expectations across cross-functional teams

· Develop, modify, configure & debug existing data pipeline as per the business requirement.

· Troubleshoot and resolve technical issues. Debug, tune and optimize code for optimal performance

· Manage the new requirements, Review the existing jobs, Perform gap analysis & Fixing performance issues, etc.

· Guide, coach, and upskill junior and mid-level data engineers on best practices, coding standards, and modern data patterns

· Document all data flow & mappings, sessions and workflows

· Ticket handling and problem ticket analysis skills in Agile /POD approach

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