Data Engineering Team Lead

As a Data Engineering Team Lead at Unybrands, you would lead Data Engineers and collaborate closely with Software Development Engineers (SDEs), Analytics Engineers (AEs), and Infrastructure Engineers (IEs) in the Unybrands technology department. The person should be hands-on, and your team will focus on building a modular, flexible data engineering infrastructure that we can iteratively improve on continuously. Your customers will include eCommerce, Marketing, Supply Chain, Finance, Investment, and Legal departments. You understand that our data is a strategic resource and will build data products to support every aspect of our business. The Data Engineering team will build Unybrands data model(s) in addition to our data infrastructure.

A successful candidate for this role will be an experienced data engineering team lead with strong technical knowledge in Data Engineering, Data Governance and Documentation, Infrastructure automation, Data Engineering best practices, Data Systems Architecture, and Development. You thrive in an environment where collaboration with other leaders and members is a key for setting the team strategy. Unybrands is an Agile organization, offers flexibility in working hours and locations, and encourages you to “think differently” in solving problems in efficient and novel ways.

About the role:

Data Engineering Team Lead position will lead the team of Data Engineers and works closely with different stakeholders in the Unybrands’ Technology department. This role will report directly to the Director of Data Engineering of the company.

Responsibilities include - but not limited to:

• This position is a senior position with extensive experience in Data Engineering and Data Infrastructure.
• Leads the team of Data Engineers, may need to manage the Data Engineers, and provide technical guidance to the team.
• Collaborate closely with Software Development Engineers (SDEs), Analytics Engineers (AEs) and Infrastructure Engineers (IEs) in the Unybrands’ Technology team.
• Focus on building a modular, flexible data engineering infrastructure that we can iteratively improve on continuously. Your customers will include eCommerce, Marketing, Supply Chain, Finance, Investment & Integration, and Legal etc.
• Understand that our data is a strategic resource and will build data products to support every aspect of our business.
• Help design and build Unybrands’ data model(s) in addition to our data infrastructure (in collaboration with Analytics and Infrastructure Engineering).
• Hands on development of any aspect related to data engineering with innovative tools.

A successful Lead Data Engineer will have:

Basic Qualifications:

• 6+ years of hands-on experience in Data Engineering including Lead Data Engineer or Senior Data Engineer etc. or related field with a track record of thinking about data as a strategic resource.
• 3+ years of management experience while leading the Data Engineers Team as a Team Lead
• Expertise in onboarding raw datasets from disparate data sources like Columnar, RDBMS DB instances, REST APIs, multi-format data sets etc.), designing data models that organize the data to maximize flexibility and minimize work for downstream consumers,
• Must have 4+ years of experience working with Multi Cloud Data Platform Technologies (like GCP, AWS or Microsoft Azure and their data services)
• Must have 3+ years of experience working on Google Cloud Platform and hands-on experience working on Big Query (and other services e.g., Airflow Cloud Composer, SQL Databases, Google Storage, Google Functions etc.)
• Expert in Developing automation and ETL pipelines using Python or other programming languages.
• Extensive experience in collaboration with software developers, analytics engineers (e.g., business intelligence and data science
• Experience in data modeling, ETL development, and data warehousing with an emphasis on thinking of data as a product on its own
• Proven success in communicating with business users, other technical teams, and senior leadership to collect requirements, describe data modeling decisions and data engineering strategy.
• Ability to handle multiple competing priorities in a fast-paced environment with minimal outside direction, while constantly advancing long term goal
• Excellent verbal and written communication skills

Preferred Qualifications

• Bachelor’s degree in computer science, Engineering, Mathematics, or an equivalent combination of technical education and work experience
• Master’s degree in computer science, Engineering, Statistics, Mathematics, or related field
• Experience defining data architectures, designing Data Warehouse dimensional models, and exploring technical feasibility trade-offs.
• Experience building and successfully delivering to customers complex, modular data systems that are structured as flexible, modular components (i.e., avoid monoliths) with documented interfaces and detailed documentation.
• Expertise in NoSQL, In Memory Databases is a plus
• Knowledge of data engineering best practices for an end-to-end data engineering organization that includes:
  • coding standard and code reviews
  • a mature build, test and deploy life cycle processes.
  • avoiding “single points of failure” and the uncontrolled growth of data tech debt
  • Ability to Lead the projects