AWS Data Engineer
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Skills Required: AWS Glue, Amazon EMR, Amazon Redshift, Amazon Aurora, Amazon S3, Pyspark, Python, SQL
Cloud and AWS Expertise:
In-depth knowledge of AWS services related to data engineering: EC2, S3, RDS, DynamoDB, Redshift, Glue, Lambda, Step Functions, Kinesis, Iceberg, EMR, and Athena.
Strong understanding of cloud architecture and best practices for high availability and fault tolerance.
Data Engineering Concepts:
Expertise in ETL/ELT processes, data modeling, and data warehousing.
Knowledge of data lakes, data warehouses, and big data processing frameworks like Apache Hadoop and Spark.
Proficiency in handling structured and unstructured data.
Programming and Scripting:
Proficiency in Python, Pyspark and SQLfor data manipulation and pipeline development.
Expertise in working with data warehousing solutions like Redshift.
Job ID: 145169347
Skills:
Aws Lambda, AWS Glue, Data Warehousing, AWS Athena, Databricks, Sql, data lakes, AWS Step Functions, AWS EMR, Amazon QuickSight, distributed processing
Skills:
snowflake , Apache Airflow, Aws Lambda, Git, Pyspark, AWS Glue, Spark, Shell scripting, Python, Sql, Matillion
Skills:
S3, Lambda, Pyspark, Python, AWS, Glue
Skills:
Machine Learning, Apache Spark, Node.js, Natural Language Processing, Data mining, Python, AWS, Technical computing tools, Container orchestration, Managed cloud DB
Skills:
Linux Administration, Github, Cloudformation, Apache Spark, Shell Scripting, Apache Airflow, Jenkins, Terraform, Docker, Ansible, Gitlab, Kubernetes, FinOps Principles, AWS Cloud Infrastructure, EKS, AWS Well-Architected Framework, Observability Tools, cost optimisation
