Software Engineer _Data Quality

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About the Company

Since our founding in 1931, Giant Eagle, Inc. has evolved into one of the top 40 largest private corporations in the U.S. and one of the country's largest food retailers and distributors. With more than 37,000 Team Members and $9.7billion in revenue, we are committed to investing in people, technology, and data to elevate our customer's experience across multiple touchpoints. It helps us follow on our commitment to serving others and improving our communities.

About Giant Eagle Bangalore

The Giant Eagle GCC in Bangalore is our global capability centre. Our team of more than 350 members at the GCC enables us to expand internal capabilities in the areas such as data analytics, merchandising and eCommerce, quality engineering, and automation to generate insights for faster decision-making and help us accelerate our business strategy. Our team in India plays a pivotal role in helping the company transition to new ways of working by redefining the food and grocery shopping experience for over 4.6 million customers.

Job Description Summary:

The Enterprise Data Management Team for Giant Eagle is critical to accelerating consistent and uniform data services and operational excellence at scale for our enterprise.This role will report into the Director of Enterprise Data Management and will collaborate across the various teams within our business, technology and data & analytic teams. This role delivers the data quality solutions and capabilities as defined by the Director/Manager and provides input into the strategic goals of the Data Quality product team at Giant Eagle – in alignment with the overall Data & Analytics strategy and business objectives.

This role is responsible to deliver best in class data quality capabilities, services and solutions for the enterprise. The Data Quality Engineer will actively engage in the project definition/scoping and requirements phase, effort estimation/adherence, issue escalation, detailed timeline definition and adherence for solutions involving data, technology and business processes. The scope includes the relevant components required to drive the data quality management maturity in support of both operational and analytical excellence at scale – across the dimensions of People, Process, Technology and Data.Data Quality metrics will be delivered in a relevant and meaningful way to the Giant Eagle Leadership Team.

Job Description:

- Experience Required: 3 to 5 years as data quality or data engineer; Experience across a variety of data quality disciplines that include: Data Quality Management, Data Quality Automation or Data designs & architecture; Azure; in particular Azure Data Factory, Azure SQL, Azure Functions, BLOB Storage & Event Grid; GITHUB; DevOps & Agile methodology; Data design for improving business operations & propelling BI / Analytics
- Experience Desired: Databricks & Graph DB; ETL, ELT & Data Integration; Retail data, systems and application experience
- Education Desired: Bachelor's degree
- General SQL Knowledge / .net / C#

Job Responsibilities

- Architect solutions that encompass Data Quality platform & broader data ecosystem
- Design & engineer new data qualities capabilities & automation: Design & development of automated data quality jobs / workflows; Design & development of data quality platform in Azure; Assist with QA, DEV and Prod environment deployments; Assist with creation of testing plans, resolve any defect associated with development
- This role will liaise across all relevant areas and with stakeholders at any level both within IT DnA team and across all function areas to deliver data quality capabilities
- Engage with collaborative and proactive approach to solving key data needs
- Define thorough workflow processes that enhance efficiency, minimize human touch and ensure high data quality results
- Bring best-in-class and right sized Data Quality solutions to life at Giant Eagle
- Design and deliver Data Quality solutions in a highly scalable, collaborative & agile manner
- Depth of retail and/or product business process knowledge across disciplines required for successful Data Quality designs.
- Leverage a data centric approach across all demands to build once and deploy many
- Ensure solutions meet stability concerns for ongoing maintenance and support.
- Adhere to agreed upon Product/Project Management principles to ensure work delivery alignment to strategic imperatives
- Produce all management reports completely, accurately and on time
- Participate in an on-call support rotation

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