Enterprise Data Engineer 630 views

The converse is setting a bold strategic vision to lead with digital to connect the marketplace by positioning converse.com as the first and best source for authentic Converse products and experiences. To ensure we’re exceeding the mark, they’ve built a best in a class analytics platform. As a key player of the Global Digital Analytics team, the Digital Data Engineering Sr Analyst will help build out and maintain the data foundation of this platform. This role will combine a unique blend of data engineering with an aptitude for platform/system architecture & business intelligence/advanced analytics, to ensure our analytics evolve at the speed of their consumers.

You are obsessed with data. You are results-oriented and you play well with others. You understand how raw data points come together to drive business insight. You take data integrity personally.

Responsibilities

• Development of data extracts and feeds from the full spectrum of systems in the Converse ecosystem, including transactional ERP systems, POS data, product, and merchandising systems, etc.
• Engineering data products for a variety of Operations analytics use cases, ranging from reporting and data visualization to advanced analytics/machine learning use cases
• Supports designing technical specifications & data transformation models for junior developers
• Ensures developments are on track and meet specifications as defined by product management and the business
• Responsible for data integrity of the current platform and QA of new releases
• Supports the development and maintenance of backlog items and solution features; participates in sprint planning activities from a development perspective.

Qualifications

• Bachelor’s degree in Information Systems, Information Technology, or Computer Science.
• Minimum 5 years of work experience in platform engineering, ETL/data modeling, or analytics engineering development
• Experience with cloud-based data architecture and tool stacks; AWS stack experience a plus
• Expert-level SQL; Experience with Python data science and data engineering libraries; Proven track record dealing with structured and unstructured data
• Experience working with a variety of database types (SQL/NoSQL, columnar, object-oriented) and diverse data formats
• Experience doing ETL with Spark and building data pipelines/orchestrations in Airflow a plus. Familiarity with ETL tools like Matillion
• Software development skills; Familiarity with DevOps toolchain and CICD
• Experience with data engineering for advanced analytics/data science use cases a definite plus
• Experience working with manufacturing/retail data a definite plus
• Proven track record of leading data integrity/QA, with exceptional attention to detail
• Proven ability to speak both business and technology, and effective liaison with both teams