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

S YNECHRON'S DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative Same Difference is committed to fostering an inclusive culture promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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