Enterprise Data Strategy & Governance - Data Engineer II - P2

Position Summary

This position is a part of the Data Strategy, Governance, and Analytics (DSGA) group. The Data Ops team is part of the DSGA, and its principal responsibility is to build and run the processes to capture the data created during the business’s day-to-day operations, validate, integrate, and bring it all together to make it available across the business for analytical purposes. The key success factor for data ops is that business can get their hands on high-quality, well-curated data in a timely, accurate, and integrated fashion.

The mission of the data ops team is to support the data and analytical needs of the business which are growing rapidly with the business growth, new products, partners, technological ecosystem, and expectations of a data-driven business environment.

The Data Ops Data Engineer is an experienced data / IT professional with a demonstrable background in data warehouses/data lakes and has been involved in analysis, design, development, and delivery tasks for data applications supporting very large volumes.

In addition to strong technical skills, the successful candidate also exhibits a highly collaborative and team-oriented attitude and has good interpersonal skills, oral and written presentation skills, and critical thinking skills. The successful technical lead is open and flexible to new ideas, and a fast learner who does not hesitate to dive into learning new tools, and practices to upgrade the bank’s data applications to the future state of data analytics.

Essential Job Functions:

• Lead, develop, and maintain high-quality and optimal solutions related to data ingestion, loading, and data curation.
• Design and develop data pipelines and the underlying architecture to support disparate patterns of analytical usage by partner teams within DSGA and business, in a stable and high-performant way.
• Work with Scrum masters, product owners, Subject Matter Experts, and other data engineers within the team to drive agile data programs.
• Ensure adherence to published development standards and database best practices resulting in consistent and efficient implementation of solutions.
• Translate business requirements into data solutions leading the development team’s data analysis and ETL design efforts.
• Provide crisp communication to stakeholders on the progress of data projects and escalates issues in a timely manner.
• Ensure that work and processes are well documented.
• Interact with process SMEs and senior/executive leaders across the business.
• Anticipate issues based on knowledge of internal data trends and propose solutions.
• Serve as an expert consultant to internal technical and line of business teams.
• Promote data validation, data quality, and governance goals, ensure the accuracy of deliverables, and communicate precisely.
• Perform other duties as assigned.

Position Requirements:

• 3+ years’ experience building Data Warehouse and Business intelligence solutions.
• 1+ years of experience with Big Data tools (Python, Spark, HDFS, Hive) and technologies.
• Expertise in Data Analysis, Database Design, and Data Architecture; strong SQL skills.
• Should be able to effectively identify test scenarios to assist with systems and user testing.
• Provides input on the development of project plans, test plans, and implementation plans including determining estimates on time frames and needed resources.
• Ability to work in a collaborative environment on complex problems.
• Ability to troubleshoot Code and Data quality issues.
• Strong communication and documentation skills.
• Solid planning, priority setting, and time management skills

Preferred

• Experience in financial industry, like retail banking or credit card business.