Job Title: DataStage Developer with average Control M experience.
Client location Richardson & Chicago IL 100 % remote.
Job Description:
As a DataStage Developer with ControlM experience you will be responsible for designing developing and maintaining ETL (Extract Transform Load) processes using IBM DataStage. You will also leverage your knowledge of ControlM to schedule monitor and manage batch jobs effectively. Your role will involve collaborating with crossfunctional teams to ensure seamless data integration high performance and data quality.
Key Responsibilities:
Design develop and implement ETL processes using IBM DataStage to support data integration and transformation needs.
Develop test and maintain DataStage jobs sequences and associated components.
Utilize ControlM to schedule manage and monitor batch jobs ensuring timely and accurate execution.
Collaborate with business analysts data architects and other stakeholders to understand data requirements and translate them into ETL solutions.
Optimize and tune DataStage jobs for performance and efficiency.
Perform data validation and quality assurance to ensure data accuracy and integrity.
Troubleshoot and resolve issues related to DataStage jobs and ControlM schedules.
Document ETL processes job schedules and operational procedures.
Participate in code reviews and provide constructive feedback to team members.
Stay current with industry trends and best practices in ETL development and job scheduling.
Qualifications:
Bachelors degree in Computer Science Information Technology or a related field.
Proven experience as a DataStage Developer with strong proficiency in IBM DataStage.
Experience with ControlM for job scheduling and management.
Solid understanding of ETL concepts data integration and data warehousing.
Proficient in SQL and database technologies (e.g. Oracle SQL Server DB2).
Strong analytical and problemsolving skills.
Excellent communication and collaboration skills.
Ability to work independently and as part of a team.
Detailoriented with a focus on data accuracy and quality.