Software Engineer (Big Data) with experience at Lowe’s India, Bengaluru, working on data engineering and big data projects. Skilled in PySpark, Hadoop, Hive, Spark, Airflow, Superset, PowerBI, Python, SQL, Java, Spring B…
Software Engineer (Big Data) with experience at Lowe’s India, Bengaluru, working on data engineering and big data projects. Skilled in PySpark, Hadoop, Hive, Spark, Airflow, Superset, PowerBI, Python, SQL, Java, Spring Boot, AWS, GCP, Docker, Jenkins, Kafka, Snowflake, and related tools and platforms.
Responsibilities:
• Extract, transform, and load diverse data sources into meaningful information with data cleaning,
normalization, and aggregation using PySpark scripts.
• Validating data with DBeaver SQL queries, ensuring accuracy deliver to third-party applications like
Salesforce and Liveramp.
• Performing diverse data visualization tasks using Superset, creating charts, dashboards, and reports to meet
business needs, while configuring CSS templates, user roles, and alerts for an enhanced user experience.
• Generating realistic mock data for visualization, illustrating diverse scenarios and use cases effectively.
• Optimize data storage using technologies like HDFS and integrate diverse sources/systems for seamless
data flow.
• Detect and resolve performance bottlenecks, optimize resource usage, and tune configurations for efficient
data processing.
• Establish monitoring, alerts, and troubleshoot data infrastructure health and performance using Airflow DAG
for timely issue resolution.
• Collaborate with cross-functional teams, including data scientists and analysts, to understand requirements,
provide support, and communicate insights.
Extract, transform, and load diverse data sources into meaningful information with data cleaning, normalization, and aggregation using PySpark scripts.
Validating data with DBeaver SQL queries, ensuring accuracy deliver to third-party applications like Salesforce and Liveramp.
Performing diverse data visualization tasks using Superset, creating charts, dashboards, and reports to meet business needs, while configuring CSS templates, user roles, and alerts for an enhanced user experience.
Generating realistic mock data for visualization, illustrating diverse scenarios and use cases effectively.
Optimize data storage using technologies like HDFS and integrate diverse sources/systems for seamless data flow.
Detect and resolve performance bottlenecks, optimize resource usage, and tune configurations for efficient data processing.
Establish monitoring, alerts, and troubleshoot data infrastructure health and performance using Airflow DAG for timely issue resolution.
Collaborate with cross-functional teams, including data scientists and analysts, to understand requirements, provide support, and communicate insights.
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