Data Engineer (Mainframe to Cloud Modernization)

Job Title: Data Engineer (Mainframe to Cloud Modernization)
Company: Ocient
Location: India (Remote)
Employment Type: Full-Time
Experience: 1–2 Years

About Ocient:

Ocient is a data analytics software solutions company that enables always-on, compute-intensive analysis of complex, large-scale data with outstanding performance that delivers up to 90% price savings. Ocient brings data transformation, loading, complex query processing, AI, OcientML® and OcientGeo® as a single, consolidated solution for deeper insights and data-driven decision making. Enterprises can deploy Ocient’s pilot-to-production solutions on premises, in the OcientCloud® or in the public cloud, with little to no resource-intensive integration. Ocient is a global, carbon-neutral company, headquartered in Chicago, and backed by leading investors including Greycroft, OCA Ventures, In-Q-Tel and Buoyant Ventures. For more information, please visit www.ocient.com.

About the Role:

Ocient is looking for Data Engineers with hands-on experience in both Mainframe technologies and modern Big Data/Python development. This role is ideal for early-career engineers who possess strong foundational technical skills and a passion for learning and growth in a data-driven environment. As a Data Engineer at Ocient, you will collaborate closely with cross-functional teams to design, develop, maintain, and optimize data workflows spanning traditional Mainframe systems as well as modern cloud-based platforms.

You will also have the opportunity to gain hands-on experience with AI-driven automation by building and deploying AI agents that create autonomous solutions to enhance data pipeline orchestration, automate repetitive engineering tasks, and accelerate data transformation processes. This enables you to develop cutting-edge skills while contributing to the next generation of data engineering capabilities.

Key Responsibilities:

• Develop, enhance, and troubleshoot Mainframe batch processes using JCL, Easytrieve, and SAS.
  • Build and maintain automation and data processing scripts using Python.
  • Support distributed data processing workloads using Apache Spark and the PySpark API.
  • Write efficient SQL queries for data extraction, analysis, and transformation.
  • Work with Google Cloud Platform (GCP) services - primarily Cloud Storage - for data movement and storage management.
  • Collaborate with data analysts, engineers, and business teams to support data initiatives and enhance data workflows.
  • Participate in documentation, code reviews, and best practices for data and code quality.
  • Investigate data issues, perform root-cause analysis, and implement corrective actions.

Required Qualification:

• Bachelor of Engineering (B.E.) or related 4-year technical degree in Computer Science, Information Technology, or a related field.
  • 1–2 years of experience in Mainframe technologies:

o JCL, Easytrieve, SAS

• 1–2 years of experience with:

o Python for scripting and automation
o Apache Spark with familiarity in PySpark
o SQL for data manipulation and querying
• Basic working knowledge of GCP, especially:
o Cloud Storage (bucket operations, file upload/download, permissions)
o General GCP console navigation and IAM basics
• Strong analytical thinking, debugging ability, and problem-solving mindset.
• Good communication skills and ability to work effectively in collaborative environments.

Preferred Skills (Nice-to-Have)

• Experience developing or maintaining ETL pipelines or data integration processes.
  • Familiarity with Git or other version control systems.
  • Exposure to Agile/Scrum development methodologies.
  • Basic understanding of distributed systems concepts and modern data warehouse architectures.
  • Experience with workflow orchestration tools (e.g., Airflow) is a plus.
  • Knowledge of CI/CD concepts and deployment workflows.