data analyst in Finance and Supply Chain analytics
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вакансия
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243 977 ₽
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описание
EPAM provides enterprise software products, open source solutions, and accelerators.
задачи
Own Qlik applications within a designated domain wave, such as Finance or Supply Chain;
Gain a deep understanding of app architecture, load scripts, QVD usage, and underlying business logic;
Assist with shadow, reverse-shadow, parallel run, and hypercare processes;
Diagnose and fix BI issues, including reload failures, data discrepancies, performance slowdowns, visual errors, and access problems, in collaboration with the platform admin;
Validate parallel runs by comparing results between the incumbent/vendor cycle and the EPAM-run cycle;
Analyze inconsistencies and compile supporting documentation for approval;
Build operational readiness through runbooks, known-issue trackers, and monitoring inputs;
Oversee incident and problem ticket management;
Participate in assess-and-rationalize (4R) initiatives across the BI landscape;
Rebuild or enhance key Finance and Supply Chain analytics assets and data models as part of modernization;
Work with the data platform team using Snowflake and governance stakeholders to standardize consumption patterns, definitions, and controls.
требования
5+ Years of practical experience building BI solutions using Qlik Sense on-prem and/or SaaS;
Strong skills in reading, troubleshooting, and enhancing Qlik load scripts, data models, and front-end performance;
Proven experience supporting BI in production/BAU environments, including incident handling, SLA compliance, and stability prioritization;
Hands-on experience with modern data warehouses and SQL-driven data validation;
Strong communication skills for collaboration with Product Leads, SMEs, QA teams, and Platform Ops;
English proficiency at a B2+ level or higher;
Nice to have: Experience with analytics transitions, vendor handovers, or service takeovers; familiarity with governance and access control frameworks such as Qlik Section Access or SOX-like environments; knowledge of test automation or data reconciliation tools used for BI validation; experience modernizing BI environments, including rationalization, rebuild strategies, and semantic layer design.