Data Engineer
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Role details
Tech stack
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Requirements
Languages & Scripting: Spark, Python, Java, Scala, Hive, Kafka, SQL Cloud Platforms: AWS Data Warehousing & Analytics: Redshift or Snowflake or Big Query Data Integration & ETL: AWS Glue, Aws EMR, Spark, Data Bricks CI/CD: AWS Code Pipeline, Jenkins, CloudFormation, Docker, Kubernetes
JD :
- Results-driven Data Engineer with a decade of expertise in Data engineering across cloud platforms with a total of 12 years in IT.
- Extensive experience utilizing Google Cloud Platform (GCP) services, including BigQuery, Dataflow, Dataprep, and Pub/Sub, for data engineering solutions.
- Proficient in building and managing GCP data pipelines with tools like Cloud Composer and Cloud Dataflow.
- Proven ability in developing and deploying applications on Google Kubernetes Engine (GKE).
- Strong background in implementing security and compliance on GCP, ensuring data privacy and regulatory adherence.
- Track record of optimizing cost and resource usage within GCP environments.
- Skilled in AWS services such as Amazon EMR, Redshift, and Glue for efficient data processing.
- Expertise in architecting scalable, cost-effective solutions on AWS, with proficiency in configuring AWS Lambda for serverless computing.
- Adept at setting up AWS Kinesis streams to process real-time data, enhancing system responsiveness and data-driven decision-making.
- Proficient in leveraging AWS DynamoDB to create scalable, low-latency NoSQL databases for dynamic applications.
- Deep expertise in optimizing and managing Amazon Redshift data warehouses to deliver high-performance analytics and business insights.
- Experienced in integrating AWS services into CI/CD pipelines, streamlining automation for continuous integration, delivery, and deployment.
- Skilled in setting up and securing AWS Virtual Private Cloud (VPC) environments.
- Proficient in managing Azure virtual machines (VMs) for cloud infrastructure operations.
- Extensive experience managing on-premises data infrastructure, including data warehouses and databases.
- Familiar with AWS DevOps practices for continuous integration and deployment.
- Expertise in using Git for version control in DBT projects, ensuring proper tracking and documentation of data model changes.
- Skilled in performance optimization and tuning of on-premises data systems.
- Proficient in data migration strategies between on-premises and cloud environments.
- Strong troubleshooting skills in resolving issues within on-premises data systems.
- Proven ability to maintain high availability and disaster recovery solutions in on-premises environments.
- Experienced in implementing CI/CD pipelines using tools like Jenkins and GitLab CI/CD.
- Adept in automated testing processes, including unit, integration, and regression testing.
- Skilled in gathering and analyzing project requirements to ensure alignment with business goals.
- Experienced in Agile project management, contributing to successful outcomes through data-driven analytics and collaborative teamwork
Skills: AWS Lambda, Agile Programming Methodologies, Amazon Web Services (AWS), Automation, Cloud Computing, Continuous Deployment/Delivery, Continuous Integration, Cost Control, Data Analysis, Data Management, Data Migration, Data Modeling, Data Processing, Data Warehousing, Database Extract Transform and Load (ETL), DevOps, Disaster Recovery, Docker, Documentation Models, Electronic Medical Records, GCP (Good Clinical Practices), Git, Google App Engine (GAE), High Availability, Identify Issues, Integration Testing, Jenkins, Microsoft Windows Azure, Migration Strategy, Multiplatform/Cross-Platform, NoSQL, Performance Analysis, Performance Tuning/Optimization, Privacy Regulations, Private Cloud, Problem Solving Skills, Project Control, Project Evaluation, Project/Program Management, Quality Assurance Methodology, Regression Testing, Requirements Management, Sales Pipeline, Snowflake Schema, Software Development, Software Engineering, Source Code/Configuration Management (SCM), Team Player, Test Automation, Testing, Unit Test, VMS Operating System, Virtual Machine (VM)
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