Capgemini
Python/Pyspark Developer
Capgemini, Atlanta, Georgia, United States, 30383
We are seeking a Senior Data Engineer with extensive experience in data integration analytical skills and data management.
The ideal candidate will have a strong background in Spark, Python, Scala, and Unix along with hands-on development experience. Exposure to object storage as well as a good understanding of data governance, lineage, and metadata management is essential. Familiarity with GL finance and regulatory reporting will be considered a significant plus.
Key Responsibilities:
Design and develop data integration workflows using PySpark. Optimize data processes in SQL Server and manage database performance.
Utilize Autosys for job scheduling and monitoring.
Collaborate with cross-functional teams to implement data governance and lineage solutions.
Develop and maintain stored procedures and perform ETL operations.
Leverage Spark and object storage technologies for big data solutions.
Ensure compliance with regulatory reporting requirements.
Qualifications:
Bachelor's degree in computer science, Information Technology, or a related field.
12+ years of experience in data engineering with a focus on Spark, Python, and Scala.
Strong knowledge of Unix/Linux operating systems.
Proficiency in developing stored procedures and ETL processes.
Understanding of data governance frameworks and metadata management.
Familiarity with GL finance and regulatory reporting is a plus.
Excellent problem-solving and communication skills.
DisclaimerCapgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
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The ideal candidate will have a strong background in Spark, Python, Scala, and Unix along with hands-on development experience. Exposure to object storage as well as a good understanding of data governance, lineage, and metadata management is essential. Familiarity with GL finance and regulatory reporting will be considered a significant plus.
Key Responsibilities:
Design and develop data integration workflows using PySpark. Optimize data processes in SQL Server and manage database performance.
Utilize Autosys for job scheduling and monitoring.
Collaborate with cross-functional teams to implement data governance and lineage solutions.
Develop and maintain stored procedures and perform ETL operations.
Leverage Spark and object storage technologies for big data solutions.
Ensure compliance with regulatory reporting requirements.
Qualifications:
Bachelor's degree in computer science, Information Technology, or a related field.
12+ years of experience in data engineering with a focus on Spark, Python, and Scala.
Strong knowledge of Unix/Linux operating systems.
Proficiency in developing stored procedures and ETL processes.
Understanding of data governance frameworks and metadata management.
Familiarity with GL finance and regulatory reporting is a plus.
Excellent problem-solving and communication skills.
DisclaimerCapgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
#J-18808-Ljbffr