Staples is business to business. You're what binds us together.
Our digital solutions team is more than a traditional IT organization. We are a team of passionate, collaborative, agile, inventive, customer-centric, results-oriented problem solvers. We are intellectually curious, love advancements in technology and seek to adapt technologies to drive Staples forward. We anticipate the needs of our customers and business partners and deliver reliable, customer-centric technology services.
Join the Staples Enterprise Data & Analytics team as a Senior Manager of Data Solutions Engineering, where you'll play a pivotal role in building and defining state-of-the-art analytical models and data solutions architecture for the growing data needs of our North American Delivery (NAD) organization. In this role, you'll be responsible for defining the data infrastructure, framework and governance processes that will form the foundation for new analytics capabilities, enabling the team to scale and manage operations efficiently. Your core ethos of providing data driven decision intelligence will advance and scale the enterprise to reach greater peaks consistently and sustainably.
As the senior leader of a team of highly skilled Data Engineers and contractors with varied experience levels, you'll guide the development of data structures and pipelines that organize, collect, and standardize data to generate insights and address reporting needs. Your team will be responsible for writing ELT (Extract / Load / Transform) processes, designing data ingestion/extraction frameworks & systems, and developing tools for real-time and batch analytics processing. You'll also oversee the integration of data from a variety of sources, ensuring that it adheres to data quality and accessibility standards.
In this role, you'll be responsible for planning and reviewing the work of your associates through code reviews and participating in scrum events and other Agile ceremonies. This is a fantastic opportunity to make a real impact on the future of Staples and drive innovation in our retail ecommerce enterprise.
What you'll be doing:
Work hand in hand with product owners, scrum master to deliver quality work and will be able to exercise independent judgment.
Ensure that project/department milestones/goals are met and adhere to approved budgets.
Interact with direct reports and peers in management / customers / vendors to share information and improve cross-departmental processes.
Define and deploy data architecture and enable top-down governance models.
Oversee design and the creation of data architecture (models) and repositories.
Develop data products from proof of concept to scalable solutions based on business priorities and impact, using modern tools and technologies on cloud.
Champion technical design whiteboarding sessions to enable open discussion with architects, engineers & technologists.
Enable data driven decision making: Advance access to information for decision making for wide populations of business users, by enabling them to access Data & Analytics via easy combinations of elements.
Increase adoption of Data & Analytics (D&A) via self-service and data catalog.
Manage data flow from internal and external sources by leveraging distributed and local data structures.
Optimize the data pipeline platform to support scalable workloads and diverse use cases.
Support mission critical applications and near real time data needs in the data platform.
Champion a good balance of federated data models vs. semantic data models owned by technology teams and understand the need for data silos owned by business partners.
Participate in design and code reviews.
Work with cybersecurity teams and infrastructure teams to secure and protect valuable data from inappropriate access or data loss.
Determine risk potential for various configurations and options for data administration and able to communicate issues to managers and team as required.
Assist and develop internal standards for data engineering as well as system documentation.
What you bring to the table:
Strong hands-on coding experience with languages like Python, PySpark, SQL, to access, extract, manipulate and summarize data.
Data processing: Snowflake, DBT, Databrick, Azure (ADF and Fabric), GCP - BigQuery
Database optimization (partitioning, group and sort keys, indexes, query optimization).
Accountability for the management of several segments in the enterprise data space.
Allocation of available resources to meet value stream & program objectives.
Experience with direct reports and peers in management / customers / vendors to share information and improve cross-departmental processes.
Qualifications:
What's needed- Basic Qualifications: • Bachelor's Degree or equivalent in Computer Sciences, Data Analytics, Management Information Systems, or related quantitative field in Data Engineering • 10+ years of experience in designing and building new scalable on-prem/cloud data engineering solutions using distributed frameworks like Spark, Hadoop etc. • Management and mentorship of direct staff
What's needed- Preferred Qualifications: • Experience working with: Airflow, Kubernetes, Cloud infrastructure (e.g., Azure, GCP), CI/CD (e.g., Azure DevOps, Git actions, Jenkins) • Hands-on experience with cloud data warehousing services like Snowflake. • Experience in SnowSQL, GCP - BigQuery, Cloud SQL, DataFlow, Pub/Sub, Cloud Functions etc. • Experience in developing User Defined Functions (UDF) in python, SQL, etc. • Understanding of upcoming data technology trends like, The Data Fabric from conceptualization to implementation, compostable Data & Analytics, Enterprise journey to Decision Intelligence, Experience in enabling a data marketplace solution, increasing reach of data products, and simplifying understanding and access for all consumers,
implementations of data API solutions to expand the reach of the data warehouse to multiple applications.
We Offer:
Inclusive culture with associate-led Business Resource Groups