Data Engineer- AWS, Snowflake, SQL, DBT, Python

Must Have - AWS, Snowflake, SQL, DBT, Python

The Data Engineer will develop ETL and data pipelines using AWS, Snowflake, and DBT. The ideal candidate has experience building data pipelines with ELT methodology.

Qualifications

• The requirements listed below are representative of the qualifications necessary to perform the job.
• Education and Experience
• Bachelor's degree (or foreign equivalent) in Computer Science, Computer Engineering, or a related field.
• 8+ years of experience with Data Engineering, ETL, data warehouse/data mart development, data lake development
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience working with Cloud Datawarehouse like Snowflake, Google BigQuery, Amazon Redshift
• Experience with AWS cloud services: EC2, S3, Lambda, SQS, SNS, etc.
• Experience with Cloud Integration Tools like Matillion, Dell Boomi, Informatica Cloud, Talend, AWS Glue
• Experience with GitHub and its integration with the ETL tools for version control
• Experience with Informatica PowerCenter, various scripting languages, SQL, querying tools
• Familiarity with modern data management tools and platforms including Spark, Hadoop/Hive, NoSQL, APIs, Streaming, and other analytic data platforms
• Experience with object-oriented/object function scripting languages: Python, Java, Scala, etc., a plus.
• Experience with Agile/Scrum is valuable.
• Ability to work with business as well as IT stakeholders.
• Strong written and oral communication skills with the ability to work with users, peers, and management.
• Strong interpersonal skills.
• Ability to work independently and as part of a team to successfully execute projects.
• Highly motivated, self-starter with problem-solving skills.
• Ability to multitask and meet aggressive deadlines efficiently and effectively.
• Extraordinary attention to detail and accuracy.

Responsibilities

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Cloud Integration ETL Tools, Cloud Data Warehouse, SQL, and AWS technologies.
• Design and develop ELT, ETL, Event driven data integration architecture solutions
• Work with the Data Analysts, Data Architects, BI Architects, Data Scientists, and Data Product Owners to establish an understanding of source data and determine data transformation and integration requirements
• Troubleshoot and tune complex SQL
• Utilize On-Prem and Cloud-based ETL platforms, Cloud Datawarehouse, AWS, GitHub, various scripting languages, SQL, querying tools, data quality tools, and metadata management tools.
• Develop data validation processes to ensure data quality
• Demonstrated ability to work individually and as a part of the team in a collaborative manner