As a Data Engineer you will be responsible for designing developing and maintaining data solutions for data generation collection and processing in Big Data environment using predominantly PySpark/Python. Your typical day will involve creating data pipelines ensuring data quality and implementing ETL processes to migrate and deploy data across systems using PySpark.
Roles & Responsibilities:
Design develop and maintain robust scalable high-performance Data Pipelines using PySpark.
Create data pipelines ensuring data quality and implement ETL processes to migrate and deploy data across systems.
Migrate Ab Initio ETL Applications into Pyspark based data pipelines
Migrate On Prem workloads into Cloud(AWS Databricks Snowflake) based on use cases.
Collaborate with cross-functional teams to identify and resolve data-related issues.
Stay updated with the latest advancements in data engineering and integrate innovative approaches for sustained competitive advantage.
Qualifications:
8 years of professional experience in Hadoop PySpark/Python development.
Proven expertise in PySpark and experience in handling huge volume of data
3 working experience in AWS Databricks/Snowflake Airflow
Familiarity with CI/CD pipelines and version control systems (e.g. Git).
Strong debugging and problem-solving skills.
Excellent communication and collaboration skills.
Good to Have Skills:
AWS EKS Experience Dockers and Containers
Job Title: Senior Data Engineer Location: Irving TX/Onsite Job Description: As a Data Engineer you will be responsible for designing developing and maintaining data solutions for data generation collection and processing in Big Data environment using predominantly PySpark/Python. Your typical da...
Job Title: Senior Data Engineer
Location:Irving TX/Onsite
Job Description:
As a Data Engineer you will be responsible for designing developing and maintaining data solutions for data generation collection and processing in Big Data environment using predominantly PySpark/Python. Your typical day will involve creating data pipelines ensuring data quality and implementing ETL processes to migrate and deploy data across systems using PySpark.
Roles & Responsibilities:
Design develop and maintain robust scalable high-performance Data Pipelines using PySpark.
Create data pipelines ensuring data quality and implement ETL processes to migrate and deploy data across systems.
Migrate Ab Initio ETL Applications into Pyspark based data pipelines
Migrate On Prem workloads into Cloud(AWS Databricks Snowflake) based on use cases.
Collaborate with cross-functional teams to identify and resolve data-related issues.
Stay updated with the latest advancements in data engineering and integrate innovative approaches for sustained competitive advantage.
Qualifications:
8 years of professional experience in Hadoop PySpark/Python development.
Proven expertise in PySpark and experience in handling huge volume of data
3 working experience in AWS Databricks/Snowflake Airflow
Familiarity with CI/CD pipelines and version control systems (e.g. Git).