Manager Data Engineering

1 day ago

delhi, India Giant Eagle GCC Full time
Manager Engineer
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 $9.7 billion 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 our commitment to serving others and improving our communities.
About Giant Eagle Bangalore
The Giant Eagle GCC in Bangalore is our global capability center. Our team of more than 370 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 Data Engineering Manager position involves leading and strategizing key data engineering initiatives, mentoring a team of data engineers, and coordinating with Data Analytics/science and consulting teams to manage and prioritize projects. The role requires understanding and translating business needs into data models, creating robust data pipelines, and developing and maintaining data lakes. It involves driving the strategy, roadmap, and execution of key data engineering initiatives. 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 and Spark, programming languages such as Scala, Python, SQL, and have strong analytical skills related to working with structured and unstructured datasets.
This position is based in Giant Eagle's offices in Bangalore, India, and presents an excellent opportunity for those looking to make a significant impact in the field of Data Engineering.
Job Responsibilities
Architectural Leadership: Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects and strategic internal and external partners. This includes designing and developing scalable data pipelines, data lakes, and robust data platforms using advanced big data tools on Azure.
Project Management: Lead large scale data engineering projects, including requirement gathering, estimating, planning, and execution. Work with stakeholders across the organization to understand their data needs and deliver effective solutions.
Technical Leadership: Oversee the design, development, and maintenance of CI/CD pipelines for data solutions.
Collaboration: Collaborate with various stakeholders across the organization, including business teams, data analysts, and the information system team, to implement data strategies and build data flows.
Best Practices: Understand and implement data engineering principles and best practices. Ensure the team's adherence to these best practices and continuous learning and improvement.
Data Engineering QC Strategy: Develop and implement quality control strategies for data engineering.
Hiring: Take a proactive role in the hiring process for data engineering roles, including creating and setting up interview questions and processes.
Creating & Implementing CI/CD Process: Develop and implement a robust CI/CD process to ensure rapid, reliable, and streamlined updates to the data environment.
Optimization: Apply advanced optimization techniques for PySpark and Azure ecosystems to ensure the performance and reliability of data solutions.
Data Modeling: Work with the Business team to implement data strategies, build data flows and develop conceptual data models.
Required Experience
Overall 10+ years of overall technology experience that includes at least 8+ years of hands-on software development, data engineering, and systems architecture.
Extensive experience in big data tools on Azure likeADLS, ADF, Synapse, and Databricks.
Proficiency in Python, SQL, and PySpark.
Experience in building data lakes, semantic layers and enabling data analytics and data science needs
Demonstrated experience managing and migrating data warehousing capabilities to the Azure or similar platforms
Experience with data pipeline and workflow management tools like Airflow, etc.
Strong analytic skills related to working with structured & unstructured datasets.
Proficiency in managing and communicating data warehouse plans to internal clients.
Experience with building processes supporting data transformation, data structures, metadata, dependency, and workload management.
A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
Well-versed with the pros and cons of various database technologies like Relational, NO SQL, and Columnar databases

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