OT Data Analyst

HCLTech is a global technology company, home to more than 226,300 people across 60 countries, delivering industry-leading capabilities centered around AI, digital, engineering, cloud and software, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, High Tech, Semiconductor, Telecom and Media, Retail and CPG, Mobility and Public Services.

Key Responsibilities:

• Data Mapping & Reconciliation: Perform cross-system lookups to align unique identifiers across various datasets (e.g., matching physical asset IDs to control system tags).
• Asset Hierarchy Building: Assist in defining “parent-child” relationships between assets to build a logical network model.
• Data Validation: Identify gaps or inconsistencies in existing data extracts—such as missing coordinates or naming mismatches and work with stakeholders to resolve them.
• Master Data Maintenance: Create and maintain a master mapping sheet that links engineering metadata with operational data points.
• Stakeholder Liaison: Act as a bridge between the IT project team and the engineering/operations teams to ensure the data model reflects the physical reality of the network.

Technical Skillsets & Experience:

• OT/Engineering Background: 5–8 years of experience working in an industrial or utility-based environment (e.g., Gas, Energy, Water, or Oil & Gas).
• Data Manipulation Mastery: Advanced Excel skills are essential (XLOOKUP, Power Query). Proficiency in VBA/Macros and SQL for data joining and cleansing is highly preferred.
• System Awareness: General familiarity with how data is structured in ERP systems (like SAP), GIS platforms, and SCADA/Control systems. You do not need to be a system administrator, but you should understand how to interpret data exports from these environments.
• Data Logic: Proven ability to work with “messy” data from different sources and create a structured, logical output.

Professional Attributes:

• Analytical Mindset: Comfortable navigating large datasets (10,000+ rows) and identifying patterns or errors.
• Detail-Oriented: High level of accuracy in data entry and mapping, understanding that this data supports critical operational decisions.
• Independent Worker: Able to take raw data extracts and progress the mapping exercise with minimal technical supervision.

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