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Senior Data Specialist - R01541773

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

Texas (USA), United States

Offer summary

Qualifications:

6+ years IT experience, Strong experience in Python, Advanced SQL skills required, Hands-on DBT development experience, Experience with Unix Shell scripting.

Key responsabilities:

Design and maintain data pipelines
Write complex SQL queries for large datasets
Develop backend components for performance
Implement security and data protection solutions
Support QA, UAT, and performance testing

Brillio Information Technology & Services XLarge https://www.brillio.com/

5001 - 10000 Employees

See more Brillio offers

Job description

Senior Data Specialist

Primary Skills

ETL Fundamentals, SQL, SQL (Basic + Advanced), Alation, Talend, Python, Data Warehousing, IICS, Modern Data Platform Fundamentals, PLSQL, Data Modelling Fundamentals

Specialization

ETL Specialization: Senior Data Engineer

Job requirements

6 plus years of overall IT experience. Strong Python experience mandatory. Write effective, scalable code in Python. Hands on experiance with Python - Pandas library in detail & Numpy. Advanced SQL skills are mandatory. Ability to write complex SQL queries to query large amounts of data Hands on DBT development experiance. Design, develop, and maintain DBT models, transformations, and SQL code to build efficient data pipelines for analytics and reporting. Mandatory hands on coding experience in Unix Shell scripting. Develop back-end components to improve responsiveness and overall performance. Hands-on-experience in designing and building data pipelines in data analytics implementations such as Data Lake and Data Warehouse and development. Salesforce CDP knowledge and Snowflake implementation will be a plus. Integrate user-facing elements into applications Writing Snowflake SQL queries against Snowflake Developing scripts like Unix, Python, etc. to do Extract, Load, and Transform data. Good to have working experiance with Airflow. Good to have exposure to AWS eco systems. Test and debug programs, Improve functionality of existing systems. Implement security and data protection solutions Coordinate with internal teams to understand user requirements and provide technical solutions Support QA, UAT and performance testing phases of the development cycle. Understand and incorporate the required security framework in the developed data model and ETL objects. Define standards and procedures; refine methods and techniques for data extraction, transformation and loading (ETL) both in batch and “near real time” modes. Design Data Integration, Data Warehousing, Analytics, Reporting & Data science strategies.