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Strong brand, metro location, hybrid role, and common junior data-operations skillset raise competition.
SQL, ETL, and Python are transferable, but BI tooling and shift operations require domain experience.
Explicit 1–3 years plus required SQL, scripting, and ETL exposure creates moderate shortlisting strictness.
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Assist in 24x7 monitoring, maintenance, and operational reporting of Enterprise BI ETL/ELT pipelines and systems.
Provide L1 incident management, investigate and resolve basic system alerts or job failures.
Support automation and documentation of operational tasks using Python, Shell scripting, GitHub, and AI/LLM tools.
1 to 3 years experience in BI, Data Operations, L1/L2 Support, or Data Engineering.
Foundational working knowledge of SQL, PL/SQL, and relational database concepts.
Hands-on or working knowledge of Python and Unix/Linux Shell scripting.
Willingness to work in shifts as part of a global 24x7 BI Operations team.
Early-career engineer aiming to develop expertise in data warehousing, ETL operations, automation scripting, and AI-assisted workflows.
Comfortable working in a 24x7 shift-based, fast-paced operations environment with incident management responsibilities.
Has basic exposure to cloud data platforms (e.g., Snowflake), ETL scheduling tools, and version control practices relevant to data engineering.