Data engineer with 3 years of experience in designing, implementing and optimizing data pipelines and systems. Proficient in data extraction, transformation and loading (ETL) processes. Skilled in utilizing variety of to…
Data engineer with 3 years of experience in designing, implementing and optimizing data pipelines and systems. Proficient in data extraction, transformation and loading (ETL) processes. Skilled in utilizing variety of tools and technologies including Python, SQL, Spark and AWS cloud services to deliver scalable and efficient data solutions. Proven ability to collaborate with cross-functional teams, identify business needs and translate them into data-driven strategies. Excited to leverage my expertise to create innovative solutions that optimize data-driven processes and contribute to the success of organization.
• Actively contributed to the development and maintenance of data pipelines ensuring efficient data extraction,
transformation and loading (ETL) processes.
• Developed codes using Python, PySpark and Spark SQL leveraging AWS cloud services and Git. Migrated codes written in SAS to PySpark.
• Minimized runtime by 65% and processed jobs using lower configurations by optimizing code, data loading and transformation processes.
• Worked on complex SQL queries to extract, transform and analyze data. Participated in data transformation activities including data cleaning and preprocessing tasks to ensure data accuracy and consistency.
• Developed DQ Utility for data quality and categorical checks.
• Collaborated with cross-functional teams to gather and analyze business requirements, and to identify and
troubleshoot SQL queries.
• Assisted in data quality checks, validation and testing procedures to ensure data integrity throughout the ETL process.
• Maintained detailed documentation of ETL processes, data sources and workflows, ensuring that processes were well-documented for future reference.
Actively contributed to the development and maintenance of data pipelines ensuring efficient data extraction, transformation and loading (ETL) processes.
Developed codes using Python, PySpark and Spark SQL leveraging AWS cloud services and Git.
Migrated codes written in SAS to PySpark.
Minimized runtime by 65% and processed jobs using lower configurations by optimizing code, data loading and transformation processes.
Worked on complex SQL queries to extract, transform and analyze data.
Participated in data transformation activities including data cleaning and preprocessing tasks to ensure data accuracy and consistency.
Developed DQ Utility for data quality and categorical checks.
Collaborated with cross-functional teams to gather and analyze business requirements, and to identify and troubleshoot SQL queries.
Assisted in data quality checks, validation and testing procedures to ensure data integrity throughout the ETL process.
Maintained detailed documentation of ETL processes, data sources and workflows, ensuring that processes were well-documented for future reference.
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