Data Engineer
3 months ago
Data Engineer -Data Analytics
Grow. Learn. Thrive. Giant Eagle is where your career can soar high. At Giant Eagle, you are so much more than an employee. You are part of the Family.
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.
Summary:
The role requires understanding and translating business needs into data models, creating robust data pipelines, and developing and maintaining data lakes.
It also involves implementing and maintaining CI/CD pipelines for data solutions. The ideal candidate will be proficient in big data tools preferably on Azure Stack like ADF, Databricks, Synapse Analytics, Azure DevOps, programming languages such as Spark (Scala/Python), SQL, and have strong analytical skills related to working with structured and unstructured datasets.
This role is for Data Engineering team that works on data needs for the whole enterprise. The group focuses on collection, organisation, governance, and access management of data to support productivity, efficiency, and decision-making for the business.
The impact you will have:
- Design, develop, implement, test, and operate large-scale, high-volume, high-performance data structures for analytics and Reporting.
- Use best engineering practices and build frameworks where necessary, for data ingestions, curation and consumption patterns
- Implement data structures using best practices in data modelling, ETL processes, and SQL and OLAP technologies, Model data and metadata for ad hoc and pre-built reporting.
- Ensure data delivered is of the highest quality
- Work with product tech teams and build robust and scalable data integration (ETL) pipelines using SQL, Python and Spark.
- Will be responsible to adhere to best coding and data practices.
- Communicate effectively with product/business/tech-teams/other Data teams.
What we look for:
- Bachelor's degree/Master’s degree in Engineering, Computer Science, or related field (or equivalent work experience in a related field)
- 2-4 years of experience in Data Engineering, data modelling, Data Warehousing and ETL pipelines
- Good proficiency in SQL, Scala/Python (PySpark), Scripting (Shell/Python), CI/CD, Git
- Has worked on data stack on Azure, like ADLS, ADF, Synpase Analytics, Databricks, Azure DevOps, or an equivalent stack
- Strong analytical, data profiling, and problem-solving skills
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