Dharmendra Singh Patel
Senior Data Engineer @Shell
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WORK HISTORY
Senior Data Engineer @Shell
London, GB
EDUCATION
Jabalpur Engineering College
Bachelor of Engineering (B.E.), Computer Science and Engineering
SKILLS
ABOUT DHARMENDRA SINGH PATEL
A highly motivated and result-orientated individual with over 14+ years of expertise in delivering scalable data solutions for leading energy companies like Shell and bp. Proficient in designing and implementing data architectures, ETL processes, and data governance policies. Skilled in cloud platforms (AWS, Azure), DevOps, and automation. Proven track record in optimizing data lakes, ensuring data quality, and compliance management. Strong leadership and mentorship abilities, fostering a culture of continuous learning. Adept at collaborating with stakeholders to develop data-driven strategies that align with business objectives. Passionate about leveraging the latest industry trends to drive innovation and efficiency- Hands-on experience in implementing highly available, cost-efficient, fault-tolerant, scalable solutions on Cloud platforms like AWS & Azure- Industry programming experience in Python programming language- Hands-on experience in automating, supporting, and optimizing mission-critical deployments in AWS & Azure, leveraging configuration management, CI/CD pipelines (Azure DevOps and Jenkins), and DevOps processes- Data Engineering hands-on using, AWS Glue, Databricks (PySpark/PySQL), Informatica BDM (Blaze, Hive, Spark, Sqoop), and Cloudera (Hive & Impala)- Working experience with NoSQL databases like AWS DynamoDB, and Azure Cosmos DB- Experience in importing and exporting data using SQOOP from HDFS to Relational Database Systems and vice-versa- Development of ETL applications & Big Data pipelines INFORMATICA PowerCenter and BDM (now DEI) at the Enterprise level- Worked on implementing Data Cleansing & Enrichment Project for data profiling, creating score cards, creating reference tables, and documenting Data Quality metrics/dimensions like Accuracy, completeness, duplication, validity, and consistency using Informatica Enterprise Data Catalogue tools for Upstream Work Management Sustain project using INFORMATICA IDQ- Good understanding of Big Data, Data Warehousing, and ETL concepts- Experience in working in SQL, Shell Scripting, and HiveQL.
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