Capgemini
Overview
6+ years of experience in data pipeline engineering for both batch and streaming applications. Hands-on coding capable in at least one core language (Python, Java or Scala) with Spark. Expertise in working with distributed data warehousing and cloud services (e.g., Snowflake, Redshift, AWS) via scripted pipelines for at least 2 years. This role intersects with the Big Data stack to enable varied analytics, ML, etc., not just DW-type workloads. Business domains of interest include Sales & Marketing, Direct to Consumer, and Adsales. Responsibilities
Handling large and complex sets of XML, JSON, and CSV from various sources and databases Solid grasp of database engineering and design Leveraged frameworks & orchestration like Airflow as required for ETL pipelines Identify bottlenecks and bugs in the system and develop scalable solutions Unit testing and documenting deliverables Capacity to successfully manage a pipeline of duties with minimal supervision Required Technical Skills
Very high test score – Python, SQL, DW concepts & logic Core language skill in Python, Java or Scala with Spark Experience with EC2, EMR, RDS, Redshift, Snowflake Strong SQL; experience with other SQL-based databases (Oracle, SQL Server, etc.) AWS Cloud knowledge Nice to have: Working knowledge of message queuing, stream processing, and scalable big data data stores Qualifications
Experience: 3-7 years (2 years min relevant experience in the role), Bachelor’s Degree Certification: SE Level 1 (or pursuing) Progressing knowledge in Business Analysis, Business Knowledge, Software Engineering, Testing, Data Management, Architecture Knowledge and Technical Solution Design Delivery & Workplace
Candidates should be flexible / willing to work across this delivery landscape which includes Agile Applications Development, Support and Deployment. Applicants for employment in the US must have valid work authorization that does not require sponsorship of a visa for employment in the US by Capgemini. Company and Equal Opportunity
Capgemini 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. This is a general description of the duties, responsibilities and qualifications required for this position. Capgemini will consider reasonable accommodations where needed. Capgemini is a global leader in consulting, digital transformation, technology and engineering services. The Group enables organizations to realize their business ambitions through a range of services from strategy to operations. Capgemini is supported by a diverse workforce of 270,000 in almost 50 countries. With Altran, the Group reported 2019 combined revenues of €17 billion.
#J-18808-Ljbffr
6+ years of experience in data pipeline engineering for both batch and streaming applications. Hands-on coding capable in at least one core language (Python, Java or Scala) with Spark. Expertise in working with distributed data warehousing and cloud services (e.g., Snowflake, Redshift, AWS) via scripted pipelines for at least 2 years. This role intersects with the Big Data stack to enable varied analytics, ML, etc., not just DW-type workloads. Business domains of interest include Sales & Marketing, Direct to Consumer, and Adsales. Responsibilities
Handling large and complex sets of XML, JSON, and CSV from various sources and databases Solid grasp of database engineering and design Leveraged frameworks & orchestration like Airflow as required for ETL pipelines Identify bottlenecks and bugs in the system and develop scalable solutions Unit testing and documenting deliverables Capacity to successfully manage a pipeline of duties with minimal supervision Required Technical Skills
Very high test score – Python, SQL, DW concepts & logic Core language skill in Python, Java or Scala with Spark Experience with EC2, EMR, RDS, Redshift, Snowflake Strong SQL; experience with other SQL-based databases (Oracle, SQL Server, etc.) AWS Cloud knowledge Nice to have: Working knowledge of message queuing, stream processing, and scalable big data data stores Qualifications
Experience: 3-7 years (2 years min relevant experience in the role), Bachelor’s Degree Certification: SE Level 1 (or pursuing) Progressing knowledge in Business Analysis, Business Knowledge, Software Engineering, Testing, Data Management, Architecture Knowledge and Technical Solution Design Delivery & Workplace
Candidates should be flexible / willing to work across this delivery landscape which includes Agile Applications Development, Support and Deployment. Applicants for employment in the US must have valid work authorization that does not require sponsorship of a visa for employment in the US by Capgemini. Company and Equal Opportunity
Capgemini 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. This is a general description of the duties, responsibilities and qualifications required for this position. Capgemini will consider reasonable accommodations where needed. Capgemini is a global leader in consulting, digital transformation, technology and engineering services. The Group enables organizations to realize their business ambitions through a range of services from strategy to operations. Capgemini is supported by a diverse workforce of 270,000 in almost 50 countries. With Altran, the Group reported 2019 combined revenues of €17 billion.
#J-18808-Ljbffr