SysMind
Possible 3 Month CTH | No Fees | Do Not Re-Post | Confidential – submit candidates under
Capgemini
template. Role Name: Data Engineer | Location: New York hybrid | Background check MANDATORY.
Job Responsibilities
Analyze existing mainframe data sources (e.g., DB2, VSAM, IMS DB, flat files, COBOL copybooks).
Design and implement ETL/ELT pipelines to extract, transform, and load data into cloud platforms.
Develop scalable data ingestion solutions using modern cloud services (e.g., object storage, data warehouses, big data frameworks, streaming platforms).
Map and transform legacy data schemas to modern cloud-native data models.
Implement data quality, validation, and reconciliation frameworks to ensure accuracy and completeness of migrated data.
Collaborate with cloud architects to align migration pipelines with target-state data architecture.
Work with DevOps teams to integrate CI/CD automation for data pipelines.
Ensure adpersonence to data governance, security, and compliance requirements during migration.
Monitor, troubleshoot, and optimize migration processes for performance and cost efficiency.
Provide technical documentation and knowledge transfer to internal teams.
Required Skills & Experience
Strong experience working with mainframe data systems (DB2, VSAM, IMS DB, sequential files, JCL).
Hands‑on experience in ETL/ELT development using tools such as Informatica, Talend, DataStage, or custom frameworks (Python, Spark, SQL).
Solid understanding of cloud data platforms (AWS, Azure, or GCP).
Expertise with data warehousing and big data technologies (Snowflake, Redshift, BigQuery, Synapse, Hadoop, Spark).
Proficiency in data modeling and schema design.
Experience with batch and streaming ingestion frameworks (Kafka, Flink, Kinesis, Pub/Sub).
Familiarity with CI/CD and Infrastructure as Code for data pipeline deployment.
Strong problem‑solving and performance tuning skills.
Excellent communication and collaboration skills to work in cross‑functional teams.
Preferred Qualifications
Previous experience in mainframe-to-cloud migration programs.
Cloud certifications (AWS, Azure, GCP – Data/Analytics or Architect tracks).
Domain knowledge in industries reliant on mainframes (banking, insurance, personalthcare).
Familiarity with Agile/Scrum methodologies.
#J-18808-Ljbffr
Capgemini
template. Role Name: Data Engineer | Location: New York hybrid | Background check MANDATORY.
Job Responsibilities
Analyze existing mainframe data sources (e.g., DB2, VSAM, IMS DB, flat files, COBOL copybooks).
Design and implement ETL/ELT pipelines to extract, transform, and load data into cloud platforms.
Develop scalable data ingestion solutions using modern cloud services (e.g., object storage, data warehouses, big data frameworks, streaming platforms).
Map and transform legacy data schemas to modern cloud-native data models.
Implement data quality, validation, and reconciliation frameworks to ensure accuracy and completeness of migrated data.
Collaborate with cloud architects to align migration pipelines with target-state data architecture.
Work with DevOps teams to integrate CI/CD automation for data pipelines.
Ensure adpersonence to data governance, security, and compliance requirements during migration.
Monitor, troubleshoot, and optimize migration processes for performance and cost efficiency.
Provide technical documentation and knowledge transfer to internal teams.
Required Skills & Experience
Strong experience working with mainframe data systems (DB2, VSAM, IMS DB, sequential files, JCL).
Hands‑on experience in ETL/ELT development using tools such as Informatica, Talend, DataStage, or custom frameworks (Python, Spark, SQL).
Solid understanding of cloud data platforms (AWS, Azure, or GCP).
Expertise with data warehousing and big data technologies (Snowflake, Redshift, BigQuery, Synapse, Hadoop, Spark).
Proficiency in data modeling and schema design.
Experience with batch and streaming ingestion frameworks (Kafka, Flink, Kinesis, Pub/Sub).
Familiarity with CI/CD and Infrastructure as Code for data pipeline deployment.
Strong problem‑solving and performance tuning skills.
Excellent communication and collaboration skills to work in cross‑functional teams.
Preferred Qualifications
Previous experience in mainframe-to-cloud migration programs.
Cloud certifications (AWS, Azure, GCP – Data/Analytics or Architect tracks).
Domain knowledge in industries reliant on mainframes (banking, insurance, personalthcare).
Familiarity with Agile/Scrum methodologies.
#J-18808-Ljbffr