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LTM
Data Architect Databricks Data Modeling 12 Years
12 years of experience as Data Architect with strong expertise in Databricks and modern data platforms
Handson experience in designing scalable data architectures on Azure ADF Databricks Synapse SQL
Strong data modeling expertise conceptual logical dimensional and data mart design
Experience working with MDW MarketingData Warehouse and enterprise data ecosystems
Design and implement Lakehouse architectures data pipelines and optimized data models
Define data standards governance and best practices for enterprise analytics
Collaborate with business and analytics teams to translate requirements into scalable data solutions
Expertise in performance optimization data partitioning and costefficient designs
Strong knowledge of ETLELT frameworks data integration and big data processing
Excellent stakeholder management and solution leadership skills
Other Details
Variable Compensation: This position includes a bonus or variable payout component based on individual and organizational performance. Actual compensation within the range will be dependent upon the individual's skills, experience, performance and internal equity.
Benefits/perks listed below may vary depending on the nature of your employment with LTIMindtree (“LTIM”):
The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training.
Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay and other forms of bonus or variable compensation.
Disclaimer: The compensation and benefits information provided herein is accurate as of the date of this posting.
LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace.
Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.
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