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:
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Highest Qualification in: (Eg. B.Tech/B.E./M.Tech/MCA/M.Sc./MS/BCA/B.Sc./Etc.)
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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., BigQuery, Snowflake).
- BI Tool Architecture (Looker Focus): Expert proficiency in Looker and LookML 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, NumPy) 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 SaaS/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.
