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susan_evans7

Susan

@susan_evans7

Build Scalable Data Pipelines and Modern Cloud Data Platforms

United Kingdom
English, Spanish, French, German, Italian, Dutch, Urdu, Chinese, Japanese
About me
I’m Susan, a Data Engineering and Modern Data Platforms Specialist and Consultant. I build scalable data pipelines, ETL/ELT, data warehouses, data lakes, lakehouses, cloud data platforms, data integration, migration and modern data architecture using Python, SQL, Azure Data Factory, AWS, GCP, Databricks, Snowflake, Airflow, dbt and Spark. Ideal for startups and businesses needing reliable, scalable data solutions. AWS Certified Data Engineer, Microsoft Certified: Azure Data Engineer Associate, Google Professional Data Engineer, Databricks Data Engineer, SnowPro Core. HIRE ME NOW!!!! ... Read more

Skills

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susan_evans7
Susan
Offline • 
Average response time: 3 hours

See my services

Data Engineering Consulting
I will build scalable data pipelines etl and modern data engineering solutions
From$75 / projectMore details
Data Warehouse
I will design cloud data warehouse data lake and modern data architecture
From$75 / projectMore details

Work experience

Data Engineering & Modern Data Platforms Specialist

Susan Hyatt • Freelance

Apr 2021 - Present • 5 yrs 6 mos

Job History & Achievements: Design and build scalable data pipelines, ETL/ELT workflows, cloud data warehouses, data lakes, lakehouse platforms and modern data architectures. Develop reliable data integration and migration solutions using Python, SQL, Apache Spark, Airflow, dbt, Databricks, Snowflake, Azure Data Factory, AWS and Google Cloud. Help businesses modernize legacy data systems, automate data workflows, improve data quality and create scalable analytics-ready platforms. Skills: Data Engineering, Data Pipelines, ETL, ELT, Data Integration, Data Migration, Data Architecture, Data Warehouse, Data Lake, Lakehouse, Cloud Data Engineering, Python, SQL, Apache Spark, PySpark, Apache Airflow, dbt, Databricks, Snowflake, Azure Data Factory, AWS, GCP, Data Modeling, Data Analytics Industry: Data & Analytics / Information Technology