We are looking for a Senior Data Engineer for the Enterprise Data Organization to build and manage data pipeline (Data ingest, data transformation, data distribution, quality rules, data storage etc.) for Azure cloud-based data platform. The candidate will require to possess strong technical, analytical, programming and critical thinking skills.
RESPONSIBILITIES
Design, develop and maintain reliable automated data solutions based on the identification, collection and evaluation of business requirements. Including but not limited to data models, database objects, stored procedures and views.
Developing new and enhancing existing data processing (Data Ingest, Data Transformation, Data Store, Data Management, Data Quality) components
Support and troubleshoot the data environment (including periodically on call)
Document technical artifacts for developed solutions
Good interpersonal skills; comfort and competence in dealing with different teams within the organization. Requires an ability to interface with multiple constituent groups and build sustainable relationships
Versatile, creative temperament, ability to think out-of-the box while defining sound and practical solutions. Ability to master new skills
Proactive approach to problem solving with effective influencing skills
Familiar with Agile practices and methodologies
EDUCATION AND EXPERIENCE REQUIREMENTS
Four year degree in Information Systems, Finance/Mathematics, Computer Science or similar
4 - 6 years of experience in Data Engineering
REQUIRED KNOWLEDGE, SKILLS or ABILITIES
Advanced SQL queries, scripts, stored procedures, materialized views, and views
Focus on ELT to load data into database and perform transformations in database
Ability to use analytical SQL functions
Snowflake experience a plus
Cloud Data Warehouse solutions experience (Snowflake, Azure DW, or Redshift); data modeling, analysis, programming
Experience with DevOps models utilizing a CI/CD tool
Work in hands-on Cloud environment in Azure Cloud Platform (ADLS, Blob)
Working knowledge of Python
Apache Airflow, Azure Data Factory, and BI tools like Tableau preferred
Profile datasets, analyze data models, troubleshoot data anomalies, and enhance data quality
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