
Data Engineer with 4+ years in ETL orchestration & big data processing
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven Data Engineer with 3.6 years of experience in ETL orchestration, data pipeline automation, and big data processing. Proficient in PySpark, Databricks, SQL, Python, Delta Lake, and Azure Data Factory (ADF). Skilled in data modeling, data warehousing, and performance tuning to drive actionable business insights.
Mahatma Gandhi Kashi Vidyapith
M.A in Art · Art
N/A – June 30, 2017
Mahatma Gandhi Kashi Vidyapith
B.A. in Art · Art
N/A – June 30, 2015
CSM
Customer Transactions Analytics
December 1, 2023 – Present
Odisha, India
Bizzsetu
Software Engineer [D.E.] | Customer Transactions Analytics
December 1, 2021 – December 1, 2023
Maharashtra, India
Master's in Data Science with Power BI – 9-month Intensive Industry Program
Console Flare
June 1, 2026 – Present
Azure Data Fundamentals
Microsoft Certified
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience across two companies, CSM and Bizzsetu, shows adaptability to different organizational contexts. The projects involve critical data engineering tasks like pipeline design, data migration, optimization, and automation, which align well with the demands of a Data Engineer role. The breadth of skills listed (Python, MySQL, Spark, PySpark, Delta Lake, ADF, ADLS, Power BI, Jira, CDC, Medallion Architecture) suggests a versatile individual capable of contributing to diverse data initiatives. The educational background in Art, while not directly technical, is complemented by relevant certifications and hands-on experience, indicating a strong drive to transition and excel in the data domain.
Soft Skills & Operational Fit
The candidate's resume mentions soft skills such as Agile Development, Collaboration, Teamwork, and Problem-Solving, which are crucial for operational fit in a data engineering role. The project descriptions highlight a results-driven approach with quantifiable improvements (e.g., 60% improved data accessibility, 99% data accuracy, 60% reduced reporting latency), indicating a focus on delivering tangible business value.