Senior Specialist - Data Engineering & Analytics

Role overview

Responsibilities

• Support data strategy and internal processes; promote self-service analytics and help business users upskill.
• Recommend ways to organize, analyze, and present data; evaluate systems and support the analytics and AI roadmap.
• Build a data community and lead business teams in delivering value from data.
• Build, optimize, and monitor scalable pipelines; implement data quality checks and validation.
• Design and maintain warehouses, lakes, storage systems, processing frameworks, and data models.
• Gather business analytics needs, manage the analytics portfolio, and translate requirements into technical specifications and data-store designs.
• Administer and develop data warehouses and BI applications; transition BI systems to Operations and Support and support enterprise environment availability and performance.

Qualifications

• Bachelor's or master's degree in computer science.
• 8 to 11 years of experience implementing advanced analytics, data engineering, and reporting solutions.
• Experience in requirements analysis with users; hands-on Python, Airflow, multiple data sources, and APIs.
• Knowledge of algorithms and basic statistics; extensive SQL and RDBMS experience, such as DB2, Oracle, or SQL Server.
• Proficiency in data wrangling, visualization, analytics, and reporting.
• Data warehousing and BI experience with Alteryx and Power BI, Tableau, or Business Objects.
• Strong query-language experience, such as PL/SQL, SQL Server, Spark SQL, or T-SQL.
• Data warehousing, ETL, analytics, or reporting certifications are desired.

Data engineering and analytics

• Data modeling includes Star/Snowflake schemas, data marts, relational and dimensional modeling, fact and dimension tables, and physical and logical models.
• Cloud data warehouse knowledge on AWS, Azure, or Google platforms is mentioned.