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aws data engineer resume example with 7+ years of experience

Jessica Claire
  • Montgomery Street, San Francisco, CA 94105 609 Johnson Ave., 49204, Tulsa, OK
  • Home: (555) 432-1000
  • Cell:
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Summary

Experienced in data engineer with 7+ years of experience in designing, developing, and implementing scalable data solutions. Proficient in various programming languages and big data technologies, including Python, Java, Hadoop, Spark, and Hive. Skilled in cloud platforms such as AWS, GCP, and Azure, with experience implementing secure and scalable data solutions on these platforms. Strong knowledge of ETL tools, including Informatica, Talend, and Apache NiFi, and expertise in optimizing database performance and managing ETL processes. Expertise in data warehousing and modeling, including Redshift, Snowflake, and Google Big Query. Proficient in various AWS services such as EC2, S3, RDS, Lambda, and DynamoDB. Experience implementing and managing highly available and scalable systems on AWS. Familiarity with serverless computing concepts and experience deploying serverless applications using AWS Lambda. Experience building and managing data pipelines using AWS services such as Kinesis, Glue, and Data Pipeline. Knowledge of AWS machine learning services, including Sage Maker and Comprehend. Familiarity with DevOps practices and experience implementing continuous integration and continuous delivery (CI/CD) pipelines on AWS using tools such as Code Pipeline and Code Deploy. Experience implementing and managing infrastructure as code using AWS CloudFormation or Terraform. Proficient in monitoring and logging solutions on AWS, including CloudWatch, CloudTrail, and X-Ray. Knowledge of networking concepts and experience implementing and managing AWS VPCs, subnets, security groups, and load balancers. Strong collaboration and communication skills, with experience working with data scientists, analysts, and business stakeholders. Proven ability to work independently and in a team environment, with experience leading data engineering projects and initiatives. Experience designing and implementing data governance policies and data quality frameworks. Familiarity with various database management systems, including MySQL, Oracle, and MongoDB. Experience working with NoSQL databases, including MongoDB and Cassandra. Expertise in building and managing data pipelines using Python and Airflow. Strong understanding of Agile methodologies and experience working in an Agile development environment. Knowledge of machine learning concepts and techniques, including feature engineering and model deployment. Proven ability to work in a fast-paced environment and manage multiple projects simultaneously. Passion for learning and keeping up to date with the latest trends and technologies in the field of data engineering.

Skills
  • TECHNICAL SKILLS:
  • Big Data Ecosystem
  • Hadoop, MapReduce, Pig, Hive, HBASE, YARN, Kafka, Sqoop, Impala, Oozie, Zookeeper, Spark, Ambari, Elastic Search, MongoDB Avro, Storm, Parquet, Snappy, AWS
  • Cloud Technologies
  • AWS, Azure, Google cloud platform (GCP)
  • Databases & Warehouses
  • Oracle 11g/10g/9i, MySQL, DB2, MS-SQL Server, HBASE, NoSQL, SQL Server, MS Access, Teradata
  • Programming / Query Languages
  • Java, SQL, Python, NoSQL, PySpark, SQL, PL/SQL, Linux shell scripts, Scala.
  • Data Engineer/Big Data Tools / Cloud / Visualization / Other Tools
  • Databricks, Hadoop Distributed File System (HDFS), Hive, Pig, Sqoop, MapReduce, Spring Boot, Flume, YARN, Hortonworks, Cloudera, Mahout, MLlib, Oozie, Zookeeper, etc. AWS, Azure Databricks, Azure Data Explorer, Azure HDInsight, Salesforce, NI-FI, Linux, Big Query, Bash Shell, Unix, Tableau, Power BI, SAS, We Intelligence, Crystal Reports.
  • Version Controllers
  • GIT, SVN, Bitbucket
  • ETL Tools
  • Informatica, Talend
  • Hadoop Distributions
  • Cloudera (CDH3, CDH4, and CDH5), Hortonworks, MapReduce, AWS EMR
Experience
AWS Data Engineer, 01/2020 to Current
Accenture Contractor JobsSeattle, WA,
  • Developed and implemented scalable and efficient data pipelines using AWS services such as S3, Glue, Kinesis, and Lambda
  • Worked with data scientists and business stakeholders to understand their requirements and design data solutions that meet their needs
  • Designed and implemented data models and data warehousing solutions using AWS services such as Redshift and Athena
  • Developed and maintained ETL workflows using AWS Glue and Apache Spark
  • Built and managed streaming data pipelines using AWS Kinesis and Apache Kafka
  • Developed and implemented data processing solutions using AWS Lambda and Apache NiFi
  • Designed and implemented data governance policies and data quality frameworks
  • Developed and implemented data security solutions using AWS services such as IAM, KMS, and S3 bucket policies
  • Worked with AWS databases such as RDS, DynamoDB, and Aurora, and implemented solutions for data replication and synchronization
  • Designed and implemented data archiving and backup solutions using AWS services such as S3 and Glacier
  • Developed and implemented data visualization solutions using AWS Quick Sight or third-party tools such as Tableau and Power BI
  • Implemented real-time data processing solutions using AWS Kinesis and AWS Lambda
  • Developed and maintained data processing workflows using Apache Airflow and AWS Glue
  • Worked with AWS machine learning services such as Sage Maker and Comprehend
  • Optimized database performance and managed ETL processes
  • Managed AWS infrastructure and resources using AWS CloudFormation or Terraform
  • Worked with DevOps teams to implement CI/CD pipelines for data solutions
  • Worked with AWS cost optimization strategies and implemented cost optimization measures
  • Experience working with AWS VPCs, subnets, security groups, and load balancers
  • Knowledge of AWS networking concepts and experience implementing and managing AWS Direct Connect, VPN, and Route53
  • Performed Hive test queries on local sample files and HDFS files
  • Used Spark Streaming to divide streaming data into batches as an input to spark engine for batch processing
  • Worked on analyzing Hadoop cluster and different Big Data analytic tools including Pig, hive, HBase, Spark and Sqoop
  • Generating various capacity planning reports (graphical) using Python packages like NumPy, matplotlib
  • Analyzing various logs that are been generating and predicting/forecasting the next occurrence of event with various Python libraries
  • Hands-on experience with Snowflake utilities, Snow SQL, Snow Pipe, Big Data model techniques using Python
  • ETL pipelines in and out of data warehouse using combination of Python and Snowflakes Snow SQL Writing SQL queries against Snowflake.
AWS Data Engineer, 05/2017 to 12/2019
Accenture Contractor JobsAustin, TX,
  • Designed and implemented data streaming and batch processing solutions using AWS Glue, Apache Spark, and Apache Flink
  • Developed and maintained data ingestion pipelines for various data sources such as web logs, application logs, and clickstream data
  • Worked with AWS services such as AWS Data Pipeline and AWS Batch to automate and schedule data processing tasks
  • Implemented data validation and verification frameworks to ensure data accuracy and consistency
  • Developed and maintained data migration and synchronization solutions for data movement across different data sources and AWS regions
  • Implemented real-time data streaming solutions using AWS Kinesis and Apache Kafka
  • Implemented data transformation and aggregation solutions using AWS Glue and Apache Spark
  • Designed and implemented data partitioning and indexing strategies to optimize query performance
  • Implemented serverless data processing solutions using AWS Lambda and API Gateway
  • Developed and maintained data integration solutions using AWS services such as AWS AppSync and AWS Step Functions
  • Worked with AWS services such as AWS Data Sync and AWS Storage Gateway to implement hybrid cloud storage solutions
  • Designed and implemented data cataloging solutions using AWS Glue Data Catalog and third-party tools such as Collibra
  • Implemented data governance policies and procedures to ensure data security and privacy
  • Worked with AWS services such as AWS Elasticsearch and Kibana to implement log analytics and search solutions
  • Developed and maintained data analytics solutions using AWS services such as Amazon EMR and AWS Glue
  • Worked with AWS services such as AWS IoT and AWS Greengrass to implement edge computing and IoT solutions
  • Developed and maintained data lineage and traceability solutions using AWS services such as AWS Lake Formation and AWS Glue Data Catalog
  • Worked with AWS services such as AWS CloudTrail and AWS Config to implement audit and compliance solutions
  • Implemented data encryption and data protection solutions using AWS services such as AWS Key Management Service (KMS) and AWS Certificate Manager
  • Designed and implemented data retention and lifecycle management policies for data storage solutions
  • Worked with AWS services such as AWS Identity and Access Management (IAM) to manage user access and permissions for data resources
  • Developed and maintained disaster recovery and business continuity plans for data solutions
  • Worked with AWS services such as Amazon ECR and AWS Code Build to implement containerization and deployment solutions
  • Implemented data streaming solutions using AWS services such as AWS IoT and AWS Kinesis Firehose
  • Developed and maintained custom data transformation and processing solutions using AWS Lambda Layers and AWS Step Functions.
Data Engineer, 12/2015 to 04/2017
Bank Of America CorporationBedford, TX,
  • Worked with AWS services such as AWS Marketplace and AWS Private Link to integrate third-party data solutions with AWS
  • Developed and maintained data visualization and reporting solutions using AWS services such as Amazon Quick Sight and AWS Glue Data Brew
  • Implemented data replication and synchronization solutions for disaster recovery and high availability using AWS services such as AWS Storage Gateway
  • Worked with AWS services such as AWS Direct Connect and AWS VPN to implement secure and reliable connectivity to AWS
  • Developed and maintained data discovery and profiling solutions using AWS services such as AWS Glue and AWS Lake Formation
  • Worked with AWS services such as AWS Elastic File System (EFS) and Amazon S3 to implement scalable and durable storage solutions
  • Implemented data backup and restore solutions using AWS services such as AWS Backup and AWS Cloud Endure
  • Worked with AWS services such as AWS Resource Groups and AWS Systems Manager to manage and automate data resources
  • Developed and maintained data access control solutions using AWS services such as AWS Network Firewall and AWS WAF
  • Worked with AWS services such as AWS Fargate and Amazon EKS to implement container orchestration and management solutions
  • Implemented data versioning and change management solutions using AWS services such as AWS Code Commit and AWS Code Pipeline
  • Worked with AWS services such as Amazon MQ and AWS SNS to implement messaging and notification solutions
  • Developed and maintained data archiving and retrieval solutions using AWS Glacier and AWS Snowball
  • Worked with AWS services such as AWS Batch and AWS Elastic Beanstalk to deploy and manage data processing applications
  • Implemented data anonymization and pseudonymization solutions to ensure data privacy.
Education and Training
Bachelors: Electronics, Expected in to JNTUH University - ,
GPA:

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Resume Overview

School Attended

  • JNTUH University

Job Titles Held:

  • AWS Data Engineer
  • AWS Data Engineer
  • Data Engineer

Degrees

  • Bachelors

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