Senior Data Engineer

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.

Design, develop, and support scalable IBM Data Stage ETL solutions and enterprise data pipelines for mission-critical applications. Collaborate with business and technology teams to deliver high-quality, performant, and reliable data integration solutions aligned with enterprise architecture standards. The ideal candidate will have extensive experience working with multiple source and target systems including Oracle, DB2, Snowflake, flat files, cloud storage, structured, semi-structured, and unstructured data sources.

The candidate should possess deep expertise in IBM Data Stage, Snowflake, Unix Shell Scripting, and PL/SQL. This role involves building scalable data pipelines, optimizing data movement processes, supporting data warehouse, data lake, and Lakehouse platforms, and enabling enterprise analytics and reporting solutions.

• Strong hands-on experience with IBM Data Stage 11.7 or above including Parallel Jobs, Sequencers, Parameter Sets, Job Monitoring, Administration, and Performance Tuning.
• Advanced SQL and PL/SQL development skills with strong experience in Oracle and DB2 environments.
• Design, develop, test, deploy, and support complex ETL/ELT solutions using Data Stage and enterprise data pipelines.
• Develop reusable ETL frameworks using IBM Data Stage, parameterized jobs, metadata-driven solutions, and automated data processing workflows.
• Analyze business and technical requirements and translate them into scalable ETL designs and data integration solutions.
• Implement data extraction, transformation, validation, cleansing, reconciliation, and loading processes using Data Stage.
• Experience integrating data from Oracle, DB2, SQL Server, Snowflake, flat files, XML, JSON, Parquet, and cloud storage platforms using Data Stage.
• Strong experience with Snowflake including Streams and Tasks, Dynamic Tables, Internal and External Stages, Secure Views, Data Sharing, and Query Performance Optimization.
• Experience designing, developing cloud-native data pipelines, and migrating data from on-premises systems to Snowflake.
• Strong Unix/Linux Shell Scripting skills for process automation, file handling, batch scheduling, operational support, and production troubleshooting.
• Experience creating high-performance batch, incremental, and CDC-based data pipelines for large-volume data processing.
• Strong understanding of ETL/ELT architecture, Data Warehousing, Dimensional Modeling, Data Lakes, and Data Lakehouse architectures.
• Experience with performance tuning, root cause analysis, production support, and incident management.
• Working knowledge of Git, CI/CD pipelines, Agile methodologies, and Dev Ops practices.
• 8-10 years engineering experience.

A Bachelor's degree in computer engineering, computer science or other related discipline is required.

After training, the candidate will be working independently and communicate/collaborate with stakeholders to understand business needs. The position is hybrid in Cincinnati, OH preferred, but open to remote candidates who will work eastern time.

• #1 requirement - IBM Data Stage experience.
• #2 requirement
  - Snowflake skills.
• #3 requirement
  - Scripting experience (Unix).
• #4 requirement
  - Advanced SQL skills.

• CI/CD experience.
• Performance optimization in Snowflake.
• Previous payments experience.