Job Description

TCS Hiring !!. SQL Expertise , Trix (Google Equivalent to Excel), Understanding of Data Pipelines
TCS - Bangalore||TCS - Hyderabad
4 - 6 years
Please read Job description before Applying
NOTE: If the skills/profile matches and interested, please reply to this email by attaching your latest updated CV and with below few details:
Name:
Contact Number:
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Highest Qualification in: (Eg. B. Tech/B. E./M. Tech/MCA/M. Sc./MS/BCA/B. Sc./Etc.)
Current Organization Name:
Total IT Experience- 4 - 6 years
TCS - Bangalore||TCS - Hyderabad
Current CTC
Expected CTC
Notice period: Immediate Joiner
Whether worked with TCS - Y/N
Technical skills (must have):
Advanced Technical Skills (Must-Have)
Expert SQL & Data Warehousing: Mastery of complex SQL including advanced window functions, query optimization for performance, and extensive experience querying large, partitioned datasets in a cloud environment (e.g., Big Query, Snowflake).
BI Tool Architecture (Looker Focus): Expert proficiency in Looker and Look ML development, specifically focused on model governance, complex view/explore design, and performance tuning of the semantic layer.
Python/Scripting: Intermediate to Advanced experience with Python (e.g., Pandas, Num Py) for data manipulation, statistical analysis, or light ETL scripting.
Data Modeling Languages: Strong understanding of YAML or similar declarative languages for defining schemas (e.g., dbt) and managing data transformation logic.
Core Analytical & Leadership Skills (Must-Have)
Analytical Leadership & Problem Structuring : Proven ability to independently structure, execute, and own large, ambiguous analytical projects from initial hypothesis to final presentation.
Executive-Level Communication : Exceptional ability to communicate complex technical findings to non-technical, executive audiences using visualization and narrative storytelling.
(Nice to Have ) Deep Business Acumen (Sales/GTM) : Expert-level understanding of the Sales lifecycle, Go-To-Market (GTM) strategies, and key Saa S/Subscription metrics (e.g., ARR, Churn, CAC, LTV) to accurately interpret and correlate data to financial outcomes.
Data Governance & Quality Ownership : Demonstrated experience in creating, implementing, and enforcing data quality rules and organizational data definitions.

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