Data Engineer – SAS ETL, Oracle Database, SQL & Control-M

Job Summary

Synechron is seeking a Data Engineer SAS ETL LPA with 46 years of relevant experience in SAS ETL and Oracle Database development. The role will focus on designing developing enhancing and supporting data integration and ETL solutions. The successful candidate will use SAS Oracle Database SQL and Control-M to deliver reliable data processes perform data validation troubleshoot issues and support enterprise-scale data integration and analytics objectives.

Software Requirements

Required

• SAS ETL: Hands-on experience developing enhancing maintaining and supporting ETL processes using SAS.

• Oracle Database: Mandatory hands-on experience with Oracle Database including queries stored procedures data models data validation and performance tuning.

• SQL: Strong experience writing queries for data extraction transformation validation reconciliation and analysis.

• Control-M: Experience scheduling monitoring managing and troubleshooting ETL jobs.

• Data Warehousing Tools and Processes: Experience with data warehouse structures ETL workflows data integration and data delivery practices.

• Development and Support Tools: Experience using tools for technical documentation issue tracking job monitoring and production support.

Preferred

• Exposure to additional enterprise data integration scheduling or data quality tools.

• Experience supporting analytics-focused data projects and large-scale data processing environments.

• Familiarity with performance monitoring and optimization tools for SAS and Oracle environments.

• Exposure to automated testing deployment or release management tools used in data engineering delivery.

Overall Responsibilities

• Develop enhance maintain and support ETL processes using SAS in line with approved business and technical requirements.

• Design and optimize Oracle Database queries stored procedures data models and related data processing components.

• Analyze business requirements and translate them into technical data integration solutions.

• Perform data validation reconciliation troubleshooting root-cause analysis and performance tuning across ETL and database processes.

• Schedule monitor and troubleshoot ETL jobs using Control-M to support reliable and timely data delivery.

• Collaborate with business analysts data teams application teams testing teams and other stakeholders to clarify requirements and resolve delivery issues.

• Apply data warehousing and ETL best practices to support data accuracy completeness consistency maintainability and operational stability.

• Investigate production issues document findings coordinate resolutions and support post-implementation validation.

• Create and maintain technical documentation data mappings process specifications job schedules support procedures and operational records.

• Contribute to continuous improvement by reducing manual processing improving job efficiency reusing ETL components and optimizing resource usage where applicable.

• Deliver reliable data integration solutions that support enterprise-scale data integration and analytics projects.

Technical Skills (By Category)

Programming Languages

Essential

• SAS programming for ETL development data transformation data validation and processing.

• Strong SQL skills for queries joins subqueries aggregations stored procedures reconciliation and data analysis.

• Ability to interpret business rules and implement them through SAS ETL processes and Oracle Database components.

Preferred

• Exposure to scripting or programming languages used for job monitoring automation data validation or operational support.

• Experience developing reusable utilities for ETL testing reporting or process monitoring.

Databases and Data Management

Essential

• Mandatory hands-on experience with Oracle Database.

• Experience designing and optimizing Oracle queries stored procedures data models and data processing logic.

• Understanding of data warehousing concepts ETL architecture staging processes data marts and target data structures.

• Experience performing data validation reconciliation completeness checks consistency checks and data quality analysis.

• Ability to analyze data lineage source-to-target mappings transformation rules and downstream data dependencies.

• Experience troubleshooting database and ETL performance issues.

Preferred

• Exposure to additional relational databases or enterprise data platforms.

• Experience with data profiling metadata data governance data quality controls or data lineage tools.

• Experience supporting large-volume data processing and analytics environments.

Cloud Technologies

Essential

• Ability to support ETL and database processes in the environments used by the assigned project.

• Understanding of data integration job scheduling monitoring and data delivery across enterprise environments.

Preferred

• Exposure to cloud-based data platforms databases data warehouses or ETL services.

• Experience supporting hybrid data environments or cloud migration initiatives.

Frameworks and Libraries

Essential

• SAS ETL development and processing capabilities.

• Control-M job scheduling and monitoring capabilities.

• Understanding of ETL design patterns data transformation methods error handling restartability dependency management and batch processing.

• Ability to develop maintainable and reusable ETL workflows.

Preferred

• Exposure to data quality testing automation or deployment frameworks used in enterprise data environments.

• Familiarity with reusable ETL frameworks job control standards or process automation utilities.

Development Tools and Methodologies

Essential

• 46 years of relevant experience in SAS ETL and Oracle development.

• Experience with requirements analysis technical design development testing deployment monitoring troubleshooting and production support.

• Experience scheduling and monitoring ETL jobs through Control-M.

• Understanding of structured software development life cycle and ETL delivery practices.

• Experience creating technical documentation data mappings job specifications support procedures and implementation records.

• Ability to collaborate with cross-functional teams to deliver accurate and timely data solutions.

Preferred

• Experience working in Agile Scrum or comparable iterative delivery environments.

• Exposure to version control release management automated testing continuous integration or deployment practices.

• Experience participating in code reviews technical walkthroughs defect resolution and continuous improvement activities.

Security Protocols

Essential

• Understanding of secure handling of enterprise data during ETL processing database development testing and support.

• Ability to follow access-control data privacy confidentiality audit and environment-specific data handling requirements.

• Awareness of secure database access credential management logging and controlled use of production and non-production data.

• Ability to comply with Synechrons applicable security data governance and operational standards.

Preferred

• Experience supporting data solutions in regulated or controlled environments.

• Exposure to data masking encryption role-based access audit logging and security validation practices.

Experience Requirements

• 46 years of relevant professional experience in SAS ETL and Oracle Database development.

• Strong hands-on experience developing enhancing maintaining and supporting SAS ETL processes.

• Mandatory practical experience with Oracle Database including SQL development stored procedures data models validation and performance tuning.

• Experience using Control-M to schedule monitor troubleshoot and manage ETL jobs.

• Experience with data warehousing ETL best practices data integration data validation and data quality activities.

• Demonstrated ability to analyze business requirements and translate them into technical data solutions.

• Experience troubleshooting ETL and database issues and supporting reliable data delivery.

• Experience collaborating with cross-functional teams including business development testing data and support teams.

• Experience in enterprise-scale data integration and analytics projects is preferred.

• Candidates may qualify through equivalent professional experience in SAS development ETL engineering database development or data integration roles where they can demonstrate comparable technical outcomes.

Day-to-Day Activities

• Develop and maintain SAS ETL workflows write and optimize Oracle SQL and stored procedures and validate data against source-to-target requirements.

• Schedule and monitor ETL jobs in Control-M investigate failures perform troubleshooting and coordinate resolution of data or processing issues.

• Participate in requirements discussions technical reviews testing activities status meetings and collaboration with cross-functional delivery teams.

• Prepare technical documentation data mappings validation results support records and implementation deliverables while making technical decisions within approved standards.

Qualifications

• Bachelors degree in Computer Science Information Technology Engineering Data Management or a related field; equivalent relevant professional experience may be considered.

• 46 years of professional experience in SAS ETL and Oracle Database development with demonstrated enterprise data integration experience.

• Relevant training in SAS ETL Oracle Database SQL data warehousing Control-M data quality and production support practices is preferred.

• Certifications in SAS Oracle Database data engineering data management or related technologies are preferred but not required.

• Commitment to continuous professional development through relevant technical training product updates data engineering practices and evolving delivery standards.

Professional Competencies

• Apply critical thinking and structured problem-solving to analyze requirements investigate data issues troubleshoot ETL failures and identify root causes.

• Collaborate effectively with business stakeholders data teams developers testers support teams and other delivery participants.

• Communicate technical findings data quality results risks dependencies progress and resolution plans clearly and accurately.

• Adapt to changing business requirements data structures ETL processes technology environments and delivery priorities.

• Identify opportunities to improve ETL performance data quality automation reusability maintainability and efficient use of processing resources.

• Manage time and priorities across requirements analysis development validation job monitoring troubleshooting documentation and delivery commitments.