DataStage Engineer

Job Summary

Synechron is seeking an experienced DataStage Engineer to design, develop, and maintain advanced data integration solutions within enterprise environments. This role involves collaborating with cross-functional teams to implement scalable, secure, and efficient data workflows that support analytics, reporting, and operational needs. The engineer will contribute to organizational data strategy by leveraging cutting-edge technologies and adhering to best practices in ETL development and data management.

Software Requirements

Required:

• Strong proficiency in IBM DataStage for designing, developing, and optimizing ETL workflows
• Knowledge of the entire data lifecycle management, including data ingestion, transformation, and loading processes
• Experience working with relational databases such as Oracle, SQL Server, or equivalent, with expertise in query optimization and data modelling
• Familiarity with scripting languages such as Shell, Python, or Perl for automation and workflow enhancements
• Understanding of data security and compliance standards relevant to enterprise data management

Preferred:

• Experience working with cloud-based data platforms (AWS Redshift, Google BigQuery, Azure Synapse)
• Knowledge of other data integration tools (Informatica, Talend, Apache NiFi)

Overall Responsibilities

• Design, develop, and implement robust ETL workflows using IBM DataStage aligned with organizational data strategies
• Collaborate with data architects, analysts, and business teams to define data requirements and translate them into efficient data pipelines
• Optimize existing data workflows for improved performance, reliability, and data quality
• Participate in code reviews, troubleshoot data management issues, and resolve technical performance bottlenecks
• Ensure compliance with data security standards and best practices for data privacy and governance
• Maintain comprehensive documentation of data workflows, system configurations, and technical procedures
• Stay current with industry trends and emerging data integration tools, recommending improvements or new solutions as appropriate

Technical Skills (By Category)

Programming Languages:

• Essential: Shell scripting, Python or Perl for workflow automation and scripting tasks
• Preferred: SQL for data transformation, query optimization, and review

Databases/Data Management:

• Proficiency in relational databases such as Oracle, SQL Server, or similar, including data modelling and performance tuning
• Experience with data warehousing solutions (e.g., Redshift, Snowflake) is a plus

Cloud Technologies:

• Knowledge of cloud-based data platforms (AWS, Azure, Google Cloud) and hybrid cloud data architectures
• Familiarity with cloud storage, managed database services, and data security practices

Frameworks and Libraries:

• In-depth knowledge of IBM DataStage and related ETL tools
• Experience with scripting libraries and APIs used for data pipeline automation

Development Tools and Methodologies:

• Version control systems such as Git
• Data integration and orchestration tools (Apache NiFi, Airflow)
• Agile methodologies (Scrum, Kanban) for project planning and delivery

Security Protocols:

• Understanding of enterprise data governance, compliance, and security standards
• Implementation of data encryption, role-based access control, and audit logging

Experience Requirements

• Minimum of 7 years of experience in data integration and ETL development
• Proven track record of designing and deploying complex data workflows in enterprise environments
• Experience working with relational and cloud data platforms
• Knowledge of data security, governance, and compliance best practices
• Experience in banking, retail, or fintech domains is advantageous
• Alternative: Demonstrated success in similar big data, analytics, or data warehousing projects with relevant certifications

Day-to-Day Activities

• Develop, test, and deploy scalable ETL workflows in IBM DataStage
• Collaborate with business analysts, data architects, and developers to understand and refine data requirements
• Troubleshoot and optimize data workflows to improve throughput and reduce system latency
• Conduct data quality assessments and data validation procedures
• Automate workflows with scripting and scheduling tools, ensuring reliable execution
• Review and enhance existing data pipelines based on performance metrics and business feedback
• Document technical designs, processes, and configurations for ongoing support and knowledge sharing

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field
• Relevant certifications such as IBM DataStage Certified Developer or equivalent are preferred
• Continuous learning and professional development in data engineering, cloud platforms, and Big Data

Professional Competencies

• Analytical thinking and troubleshooting skills to resolve complex data integration issues
• Ability to work independently and collaboratively across teams
• Excellent communication skills to explain technical concepts to non-technical stakeholders
• Adaptability to evolving data technologies and organizational data strategies
• Innovation mindset focused on improving data pipelines, security, and efficiency
• Strong organizational skills to prioritize tasks and meet project deadlines

Key Skills/Competency

• IBM DataStage
• ETL Development
• Data Integration
• Data Warehousing
• SQL
• Shell Scripting
• Python
• Cloud Platforms (AWS, Azure, GCP)
• Data Security
• Data Governance