Job Summary

Synechron is seeking a Data Engineer – SAS ETL – LPA with 4–6 years of relevant experience in SAS ETL and Oracle Database development. The role will focus on designing, developing, enhancing, and supporting enterprise-scale data integration and ETL solutions. The successful candidate will use SAS, Oracle Database, SQL, and Control-M to deliver reliable data processes, support data quality, troubleshoot issues, and contribute to analytics and data delivery 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 and optimizing SQL 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 to meet approved business and technical requirements.

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

• Analyze business requirements and translate them into scalable, maintainable, and technically accurate 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 delivery and analytics objectives.

Technical Skills (By Category)

Programming Languages

Essential

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

• Strong SQL skills for complex 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

• 4–6 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, sprint planning, 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 Synechron’s 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

• 4–6 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

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

• 4–6 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.