Key Accountabilities:

• Active contributor to code development in projects and services.
• Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products.
• Build and own the automation and monitoring frameworks that capture metrics and operational KPIs for data pipeline quality and performance.
• Responsible for adopting best practices around systems integration, security, performance, and data management defined within the organization.
• Empower the business by creating value through the increased adoption of data, data science, and business intelligence landscape.
• Collaborate with internal clients (data science and product teams) to drive solutions and POC discussions.
• Develop and optimize procedures to “productionalize” data engineering pipelines.
• Define and manage SLA’s for data products and processes running in production.
• Support large-scale experimentation was done by data scientists.
• Prototype new approaches and build solutions at scale.
• Research in state-of-the-art methodologies.
• Create documentation for learning and knowledge transfer.

Qualifications

• 5+ years of overall technology experience that includes at least 2+ years of hands-on software development, data engineering.
• 2+ years of experience in SQL optimization and performance tuning, and development experience in programming languages like Python, PySpark, Scala, etc.).
• 1+ years in cloud data engineering experience in Azure. Azure Certification is a plus.
• Experience with version control systems like Github and deployment & CI tools.
• Experience with data modeling, data warehousing, and building high-volume ETL/ELT pipelines.
• Experience with data profiling and data quality tools is a plus.
• Experience in working with large data sets and scaling applications like Kubernetes is a plus.
• Experience with Statistical/ML techniques is a plus.
• Experience with building solutions in the retail or in the supply chain space is a plus
• Understanding metadata management, data lineage, and data glossaries is a plus.
• Working knowledge of agile development, including DevOps and DataOps concepts.
• Familiarity with business intelligence tools (such as PowerBI).

Skills, Abilities, Knowledge:

• Excellent communication skills, both verbal and written, and the ability to influence and demonstrate confidence in communications with senior level management.
• Comfortable with change, especially that which arises through company growth.
• Ability to understand and translate business requirements into data and technical requirements.
• High degree of organization and ability to coordinate effectively with team.
• Positive and flexible attitude and adjust to different needs in an ever-changing environment.
• Foster a team culture of accountability, communication, and self-management.
• Proactively drive impact and engagement while bringing others along.
• Consistently attain/exceed individual and team goals

Differentiating Competencies Required

• Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business.
• Understands both the engineering and business side of the Data Products released.
• Places the user in the center of decision making.
• Teams up and collaborates for speed, agility, and innovation.
• Experience with and embraces agile methodologies.
• Strong negotiation and decision-making skill.
• Experience managing and working with globally distributed teams.