Anik Dian

Angestellt, Enterprise Architect Manager - BI, Puma
Erlangen, Deutschland

Fähigkeiten und Kenntnisse

Data governance
Data Quality
Data Catalog
ETL-Tools
ETL (Extract, transform, load)
Data Warehouse
Microsoft Azure
Azure Data Factory
Microsoft Power BI
SSIS
SSMS
SQL
Microsoft BI
Databricks
Team work
Communication skills
Flexibility

Werdegang

Berufserfahrung von Anik Dian

  • Bis heute 1 Jahr und 10 Monate, seit Feb. 2024

    Enterprise Architect Manager - BI

    Puma

    My work centers around designing and implementing data governance frameworks and enhancing data quality across systems using Ataccama. Partner with business stakeholders to define data quality use cases and translate them into scalable technical solutions using Ataccama. Collaborate with IT and cross-functional teams to establish data standards, governance policies, and data stewardship processes aligned with enterprise architecture principles.

  • 2 Jahre und 1 Monat, Dez. 2021 - Dez. 2023

    BI/ETL Developer

    EY Ernst & Young

    Experienced in Extract, Transform, Load (ETL) processes using SSIS, Azure Data Factory (ADF), and Informatica PowerCenter, integrating data from multiple sources into enterprise Data Warehouses. Developed interactive Power BI reports, dashboards, and KPI scorecards, applying advanced calculations such as aggregate, date, logical, numeric, and string functions. Contributed to the migration of on-prem SQL Server and SSIS packages to Azure SQL Database.

  • 3 Jahre und 1 Monat, Dez. 2018 - Dez. 2021

    ETL developer

    Tata Consultancy Services Ltd

    Utilized a wide range of SSIS transformations including Lookup, Derived Column, Data Conversion, Conditional Split, Merge, Merge Join, Multicast, Sort, Filter, Union All, and Aggregate to build robust and scalable ETL workflows. Created, deployed, and scheduled SSIS packages using SQL Server Agent, and published analytical reports using Power BI for business stakeholders. Experienced in troubleshooting data quality, validation, pipeline failures, and performance issues within Azure Data Factory (ADF).

Sprachen

  • Englisch

    Fließend

  • Deutsch

    Grundlagen

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