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t_dataengineer

TanyaZ

@t_dataengineer

Senior Data Engineer, BI and Analytics Engineering, SQL, Python, ETL Pipelines

Vereinigte Staaten
Englisch
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
Services Offered: SQL Optimization: • Query execution plan analysis and index optimization • Identifying and resolving complex database deadlocks and lock contention • Refactoring stored procedures and slow-running SQL code for MySQL, and MS SQL Server Data Engineering & ETL/ELT Automation: • Designing scalable data pipelines (SSIS, Python, AWS services) • Data warehouse (DWH) modeling, schema design, and data mart construction BI & Reporting: • End-to-end BI solution deployment (SSRS, Tableau) • Transforming raw operational data into optimized analytical models and dashboards... Mehr lesen

Kompetenzen

t
t_dataengineer
TanyaZ
offline • 

Meine Dienstleistungen

Datenbank-Design
I will optimize slow sql queries performance
Ab100 $ / ProjektWeitere Details

Arbeitserfahrung

GlobalLogic

Senior Business Intelligence / Data Engineer

GlobalLogic • Vollzeit

Oct 2019 - Jul 2024 • 4 yrs 9 mos

Designed and maintained data models for a data warehouse integrating multiple source systems. Defined data structure, relationships, and transformation logic to ensure consistent and reliable reporting and analytics, enabling a single trusted source of data for downstream consumers. ● Owned the design and implementation of 300+ ETL workflows (SSIS packages) processing data from multiple systems into the data warehouse. Defined data flow and transformation logic to ensure efficient and reliable processing, achieving 99%+ data accuracy in production pipelines. ● Optimized complex SQL queries using indexing strategies and execution plan tuning, improving query performance by up to 70% and reducing analytical query runtime. ● Built configuration-driven ETL pipelines using YAML-based definitions instead of hardcoded logic, reducing duplicate code and improving scalability and maintainability across multiple data sources. ● Owned data quality for production ETL datasets by implementing automated SQL-based validation checks between source systems and the data warehouse, reducing manual verification effort and ensuring 99%+ data accuracy in production. ● Collaborated with cross-functional teams (business stakeholders, analysts, and engineers) to translate requirements into data models and analytical solutions. Identified data gaps and shaped data structures to support new reporting and analytics capabilities, improving data availability for downstream users. ● Built curated datasets and analytical data models used in reporting and analytics tools, enabling business users to independently access and analyze data and reducing dependency on engineering for ad-hoc data requests. ● Automated data validation and monitoring workflows using SQL and Python-based checks, improving data reliability, reducing manual operational effort, and enabling proactive detection of data consistency issues across source systems and the data warehouse. ● Mentored new team members through technical