Lead AWS Data Engineer

Job Title: Lead AWS Data Engineer
Duration- Fulltime Permanent
Location: Owings Mills, MD (Onsite from Day 1/Hybrid)

Job Description:
Lead AWS Data Engineer-

• 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.

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