Big Data Engineer Resume Samples

Description :

1. Led the design and implementation of a Big Data platform using Hadoop and Spark.
2. Utilized technologies such as Hive, Kafka, and Storm for data processing and analytics.
3. Managed data storage solutions with MongoDB and PostgreSQL, ensuring high availability.
4. Developed complex data processing jobs using Java MapReduce and PySpark.
5. Created efficient database schemas for large-scale data repositories.
6. Engineered a real-time anomaly detection system using Storm for proactive data monitoring.
7. Designed custom libraries for data ingestion into ElasticSearch to enhance search capabilities.

Experience

2-5 Years

Level

Junior

Education

Data Science

Description :

1. Engineered a high-performance Hadoop ecosystem, enhancing data processing capabilities.
2. Implemented data ingestion strategies using Sqoop, integrating diverse datasets into HDFS.
3. Developed complex Hive queries for data analysis, identifying trends and anomalies.
4. Optimized Pig scripts for data transformation, improving processing speed by 25%.
5. Configured and managed a multi-node Hadoop cluster, ensuring high availability and reliability.
6. Collaborated with business stakeholders to define data requirements and deliver actionable insights.
7. Monitored system performance and executed troubleshooting processes to ensure data integrity.

Experience

7-10 Years

Level

Management

Education

M.S. in Computer Science

Description :

1. Enhanced customer insights by integrating data from diverse public domains.
2. Developed and implemented a robust MapR environment for big data processing.
3. Executed Hadoop jobs to efficiently process terabytes of data daily.
4. Transformed and loaded large sets of structured and semi-structured data.
5. Managed data ingestion from multiple sources while ensuring data integrity.
6. Utilized MapR-FS for querying data efficiently from various servers.
7. Collaborated with cross-functional teams to ensure data governance compliance.

Experience

2-5 Years

Level

Junior

Education

M.S. in Data Science

Description :

1. Engineered scalable data storage solutions for fluctuating data volumes.
2. Implemented robust data ingestion processes using HDFS and various file systems.
3. Developed custom UDFs in Hive and Pig to enhance data processing capabilities.
4. Utilized Sqoop for efficient data transfer from RDBMS to HDFS, streamlining workflows.
5. Managed ETL processes, ensuring accurate data transformation and loading for analytics.
6. Collaborated with cross-functional teams to design data models that meet business needs.
7. Optimized performance of Hadoop clusters, achieving significant cost savings and efficiency gains.

Experience

7-10 Years

Level

Management

Education

Data Science

Description :

1. Installed and configured Hadoop MapReduce, developing multiple MapReduce jobs in Java for data cleaning and pre-processing.
2. Designed complex MapReduce jobs using Hive for efficient data handling.
3. Utilized Sqoop to import data from RDBMS into HDFS, ensuring smooth data transitions.
4. Performed transformations and filtering on imported data with Hive and MapReduce, loading final datasets into HDFS.
5. Developed Pig UDFs for data preprocessing and analysis, enhancing data quality.
6. Created comprehensive reports for BI teams using Sqoop to export data into HDFS and Hive.
7. Migrated ETL processes from Oracle to Hive, streamlining data manipulation with Talend.

Experience

5-7 Years

Level

Executive

Education

B.Sc. Computer Science

Description :

1. Designed and implemented scalable data pipelines using Hadoop and Spark, enhancing data processing efficiency.
2. Configured and optimized Hive and HBase for structured and semi-structured data handling.
3. Collaborated with cross-functional teams to gather requirements and develop data solutions aligned with business objectives.
4. Developed and maintained ETL processes for data integration into data warehouses, ensuring data quality and accessibility.
5. Utilized advanced analytics tools to extract insights from large datasets, driving decision-making processes.
6. Conducted performance tuning and optimization of SQL queries to improve data retrieval times.
7. Provided training and support for team members on best practices in big data technologies and analytics.

Experience

7-10 Years

Level

Management

Education

M.Sc. in Data Science

Description :

1. Designed and implemented robust data pipelines for processing large-scale datasets.
2. Developed analytical reports to identify trends in banking services and customer behavior.
3. Leveraged Spark for real-time data processing and analytics, improving transaction monitoring.
4. Created and optimized Scala applications within a Spring framework for data processing.
5. Executed shell scripts to automate data extraction from ERP systems to HDFS.
6. Managed data storage in Hive, facilitating advanced analytical queries and reporting.
7. Managed data storage solutions on AWS, achieving a 20% cost reduction in data storage expenses.

Experience

7-10 Years

Level

Management

Education

M.S. in Data Science

Description :

1. Led teams in developing scalable data pipelines for high-volume data ingestion and processing.
2. Utilized advanced data processing frameworks, ensuring efficient data flow and transformation.
3. Architected and implemented robust data storage solutions, optimizing data retrieval and analysis.
4. Monitored and enhanced data quality metrics, ensuring accuracy and reliability of data systems.
5. Streamlined data workflows, significantly reducing processing time and resource consumption.
6. Mentored junior engineers, fostering a culture of innovation and continuous improvement.
7. Led a team in migrating legacy systems to Hadoop, improving data accessibility and processing capabilities.

Experience

7-10 Years

Level

Management

Education

Data Engineering

Description :

1. Designed and implemented robust ETL pipelines for batch and real-time data processing using Google Cloud Platform tools like BigQuery and Dataproc.
2. Ensured data quality and integrity by developing comprehensive testing frameworks and validation processes.
3. Collaborated with cross-functional teams to translate business requirements into scalable data solutions, improving operational efficiency.
4. Utilized advanced analytics to identify trends and insights, driving data-informed decision-making across the organization.
5. Automated data ingestion and processing workflows, reducing manual efforts and increasing productivity.
6. Engineered big data solutions utilizing HBase to manage millions of records, enhancing data accessibility for analytics.
7. Mentored junior data engineers, fostering a culture of continuous learning and improvement within the team.

Experience

7-10 Years

Level

Management

Education

Data Science

Description :

1. Transformed raw data into actionable insights to support strategic business decisions.
2. Designed, deployed, and optimized ETL workflows using Hive, Pig, Sqoop, and Spark.
3. Created MapReduce jobs for data cleansing in Python, Java, and C, improving data quality.
4. Developed dimension and fact tables for effective data modeling and reporting.
5. Architected and implemented DataMart solutions, enhancing performance and query efficiency.
6. Identified reporting requirements and developed dashboards using BI tools for data visualization.
7. Troubleshot critical data ingestion issues, ensuring smooth data pipeline operations.

Experience

5-7 Years

Level

Executive

Education

M.S. Data Science