Our client seeks a skilled Senior Data Engineer to join the Application Health Scorecard team, pivotal in driving capacity-related initiatives to reduce technology debt across critical applications and infrastructure. By developing scorecards and dashboards, you will prioritize and manage tech debt based off consumption while collaborating closely with engineering groups spanning enterprise wide. You will optimize data querying, modeling, and ETL/ELT processes, ensuring data integrity and scalability. Your contributions will enhance operational efficiency and decision-making, supporting strategic goals through advanced analytics and future AI-driven solutions.
Responsibilities:
Develop and maintain Application Health Scorecards to prioritize critical applications based on tech debt.
Collaborate with cross-functional teams to gather tech debt data and insights.
Utilize SQL extensively for querying, data modeling, and performance optimization.
Implement ETL/ELT processes and ensure data quality and integrity.
Manage databases and data warehouses, optimizing for performance and scalability.
Work on stored procedures and scripts to automate data processes.
Required Skills:
Strong proficiency in SQL (Intermediate to Advanced level).
Proficiency in Python for data manipulation and automation tasks.
Experience with cloud platforms, preferably Azure; familiarity with AWS or Google Cloud is acceptable.
Solid understanding of ETL/ELT processes and data warehousing principles.
Ability to manage databases effectively, ensuring data availability and security.
Curious and strategically driven aptitude.
Nice to Have:
Experience with data visualization tools such as Tableau, Power BI, Qlik, or Looker.
Knowledge of AI engineering, including practical applications for data staging and cleansing.
Familiarity with ML algorithms for predictive analytics and trend analysis.