Python
Amazon Web Services (AWS)- Work in collaboration with the application team and integration team to design, create, and maintain optimal data pipeline architecture and data structures for Data Lake/Data Warehouse.
- Work with stakeholders including the Sales, Product, and Customer Support teams to assist with data-related technical issues and support their data analytics needs.
- Assemble large, complex data sets from third-party vendors to meet business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Elasticsearch, MongoDB, and AWS technology.
- Streamline existing and introduce enhanced reporting and analysis solutions that leverage complex data sources derived from multiple internal systems.
Requirements
- 5+ years of experience in a Data Engineer role.
- Proficiency in Linux.
- Must have SQL knowledge and experience working with relational databases, query authoring (SQL) as well as familiarity with databases including Mysql, Mongo, Cassandra, and Athena.
- Must have experience with Python/Scala.
- Must have experience with Big Data technologies like Apache Spark.
- Must have experience with Apache Airflow.
- Experience with data pipeline and ETL tools like AWS Glue.
- Experience working with AWS cloud services: EC2, S3, RDS, Redshift.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Full Stack Developer - Averlon