Data Engineer with Python and Abinitio

## Job Description: Data Engineer – Python with Ab Initio Exposure

We are seeking a skilled Data Engineer with strong Python experience and exposure to Ab Initio. The ideal candidate will design, develop, and maintain reliable data pipelines, ETL processes, and data integration solutions using modern Python-based technologies while supporting enterprise data platforms.

### Key Responsibilities
- Design, develop, and maintain scalable batch and near-real-time data pipelines using Python.
- Build ETL/ELT processes for data extraction, transformation, validation, and loading.
- Work with relational databases, data warehouses, APIs, files, and distributed data platforms.
- Develop reusable Python modules, frameworks, and automation utilities for data engineering workflows.
- Support and enhance existing Ab Initio applications, graphs, and workflows under guidance from senior team members.
- Collaborate with business analysts, data architects, developers, and stakeholders to understand data requirements.
- Implement data quality checks, reconciliation, error handling, logging, and exception management.
- Optimize pipeline performance, scalability, reliability, and resource utilization.
- Perform root cause analysis and resolve data-related production issues.
- Integrate data pipelines with enterprise systems, databases, cloud platforms, and scheduling/orchestration tools.
- Participate in code reviews, testing, deployment, and production support activities.
- Document technical designs, data mappings, operational procedures, and workflows.
- Follow data governance, security, compliance, and engineering standards.

### Required Skills and Qualifications
- 4+ years of experience in data engineering, ETL development, or data integration.
- Strong programming experience in Python, including scripting, object-oriented programming, data processing, and automation.
- Good knowledge of SQL, relational databases, data warehousing, dimensional modeling, and ETL concepts.
- Experience with Python data libraries such as Pandas and PySpark, or equivalent distributed processing frameworks.
- Exposure to Ab Initio tools, including GDE, Co>Operating System, EME, or Conduct>It.
- Understanding of Ab Initio graphs, components, metadata, workflows, and operational processes.
- Experience implementing data validation, reconciliation, error handling, and monitoring.
- Familiarity with Git, CI/CD, testing practices, and Agile delivery methods.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and collaboration skills.

### Preferred Skills
- Experience with Apache Airflow, Control-M, or other workflow orchestration tools.
- Exposure to Spark, Kafka, cloud data platforms, or containerized environments.
- Familiarity with data modeling, metadata management, data lineage, and data quality frameworks.
- Experience working in financial services, banking, or other highly regulated environments.
- Knowledge of performance tuning for Python, SQL, Spark, or Ab Initio workloads.
- Experience supporting enterprise-scale data migration or modernization initiatives.

### Education
Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.

### Experience Level
Mid-level Data Engineer with strong Python expertise and working exposure to Ab Initio; candidates with deeper Ab Initio experience are welcome.
 

## Job Description: Data Engineer – Python with Ab Initio Exposure

We are seeking a skilled Data Engineer with strong Python experience and exposure to Ab Initio. The ideal candidate will design, develop, and maintain reliable data pipelines, ETL processes, and data integration solutions using modern Python-based technologies while supporting enterprise data platforms.

### Key Responsibilities
- Design, develop, and maintain scalable batch and near-real-time data pipelines using Python.
- Build ETL/ELT processes for data extraction, transformation, validation, and loading.
- Work with relational databases, data warehouses, APIs, files, and distributed data platforms.
- Develop reusable Python modules, frameworks, and automation utilities for data engineering workflows.
- Support and enhance existing Ab Initio applications, graphs, and workflows under guidance from senior team members.
- Collaborate with business analysts, data architects, developers, and stakeholders to understand data requirements.
- Implement data quality checks, reconciliation, error handling, logging, and exception management.
- Optimize pipeline performance, scalability, reliability, and resource utilization.
- Perform root cause analysis and resolve data-related production issues.
- Integrate data pipelines with enterprise systems, databases, cloud platforms, and scheduling/orchestration tools.
- Participate in code reviews, testing, deployment, and production support activities.
- Document technical designs, data mappings, operational procedures, and workflows.
- Follow data governance, security, compliance, and engineering standards.

### Required Skills and Qualifications
- 4+ years of experience in data engineering, ETL development, or data integration.
- Strong programming experience in Python, including scripting, object-oriented programming, data processing, and automation.
- Good knowledge of SQL, relational databases, data warehousing, dimensional modeling, and ETL concepts.
- Experience with Python data libraries such as Pandas and PySpark, or equivalent distributed processing frameworks.
- Exposure to Ab Initio tools, including GDE, Co>Operating System, EME, or Conduct>It.
- Understanding of Ab Initio graphs, components, metadata, workflows, and operational processes.
- Experience implementing data validation, reconciliation, error handling, and monitoring.
- Familiarity with Git, CI/CD, testing practices, and Agile delivery methods.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and collaboration skills.

### Preferred Skills
- Experience with Apache Airflow, Control-M, or other workflow orchestration tools.
- Exposure to Spark, Kafka, cloud data platforms, or containerized environments.
- Familiarity with data modeling, metadata management, data lineage, and data quality frameworks.
- Experience working in financial services, banking, or other highly regulated environments.
- Knowledge of performance tuning for Python, SQL, Spark, or Ab Initio workloads.
- Experience supporting enterprise-scale data migration or modernization initiatives.

### Education
Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.

### Experience Level
Mid-level Data Engineer with strong Python expertise and working exposure to Ab Initio; candidates with deeper Ab Initio experience are welcome.

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