Junior BI Operations Engineer

Your Contribution

Move fast. Speak up. Decide and own. Drive change. Exceed customer needs. These are some of the winning behaviors you’ll need for success. In this role, you will:

• Operations & Monitoring: Assist in daily 24x7 monitoring and operational reporting for ETL/ELT data pipelines and BI systems.
• Incident Management: Serve as 1st-level (L1) support for business users and applications—investigating, triaging, and resolving basic system alerts or job failures.
• ETL Scheduling & Runbooks: Help prepare and maintain job scheduling modules; document and update runbooks with runtime statistics and operational steps.
• Knowledge Transfer: Participate in KT sessions with Data Engineering and Development teams for seamless handovers to the Ops environment.
• Automation & Scripting: Support the automation of routine operational checks using Python, Shell scripting, and version control best practices via GitHub.
• AI-Assisted Operations: Leverage modern AI and LLM tools to assist in log analysis, query optimization, bug fixing, and process documentation.
• Communication: Bridge technical issues with non-technical business users with clear verbal and written communication.

Key Qualifications

Required Skills & Experience:

• Experience: 1 to 3 years of relevant experience in BI, Data Operations, L1/L2 Support, or Data Engineering.
• Database & SQL: Foundational to working knowledge of SQL, PL/SQL, and relational database concepts.
• Data Warehousing: Basic understanding of data warehousing concepts (e.g., dimensional modeling, staging, star schema).
• Scripting & Programming: Hands-on experience or working knowledge of Python and Unix/Linux Shell scripting for automation tasks.
• Version Control: Familiarity with GitHub or Git workflows for code repository management and version tracking.
• AI & LLMs: Basic knowledge or practical exposure to AI & Large Language Model (LLM) tools (e.g., using LLM assistants for code debugging, prompt-assisted scripting, or log pattern detection).
• Cloud & Snowflake: Exposure to or working knowledge of cloud data platforms like Snowflake DB.
• ETL & Scheduling Tools: Exposure to ETL tools (e.g., Pentaho Data Integration, Talend, Informatica) and job schedulers (e.g., Airflow, Control-M, Autosys).
• Support & Analytical Mindset: Strong analytical and troubleshooting skills with a willingness to learn root-cause analysis and bug fixing.
• Shift Work: Willingness to work in shifts within a 24x7 operational rotation.

Preferable Skills:

• Hands-on experience with Pentaho Data Integration (PDI) scheduling.
• Basic understanding of CI/CD concepts applied to data pipelines.
• Familiarity with ticketing tools like Jira, ServiceNow, or similar ITSM platforms.

Education

Bachelor’s or Master’s Degree in Computer Science, Information Systems, Data Analytics, or a related technical field (or equivalent practical industry experience).