Lead - AWS Data Engineer

Data ModelingDesign and implement efficient data models ensuring data accuracy and optimal performance
ETL DevelopmentDevelop maintain and optimize ETL processes to extract transform and load data from various sources into our data warehouse
SQL ExpertiseWrite complex SQL queries to extract manipulate and analyze data as needed
Python DevelopmentDevelop and maintain Python scripts and applications to support data processing and automation
AWS ExpertiseLeverage your deep knowledge of AWS services such as S3 Redshift Glue EMR and Athena to build and maintain data pipelines and infrastructure
Infrastructure as Code IaCExperience with tools like Terraform or CloudFormation to automate the provisioning and management of AWS resources is a plus
Big Data ProcessingKnowledge of PySpark for big data processing and analysis is desirable
Source Code ManagementUtilize Git and GitHub for version control and collaboration on data engineering projects
Performance OptimizationIdentify and implement optimizations for data processing pipelines to enhance efficiency and reduce costs
Data QualityImplement data quality checks and validation procedures to maintain data integrity
CollaborationWork closely with data scientists analysts and other teams to understand data requirements and deliver highquality data solutions
DocumentationMaintain comprehensive documentation for all data engineering processes and projects
Qualifications
At least 6-9 years of experience in data engineering roles with a strong emphasis on AWS technologies
Proficiency in data modeling SQL and Python
Demonstrated expertise in AWS services especially for data processing extract transform and load
Familiarity with Infrastructure as Code IaC tools
Experience with PySpark and big data processing is a plus
Strong version control skills using Git and GitHub
Excellent problemsolving and communication skills
Ability to work independently and in a team taking ownership of projects and delivering on time