Analytics Engineer

1 month ago

New York, United States Saks Full time

Who We Are:

Saks is a world-renowned luxury ecommerce destination. The company’s unique approach combines a focus on the digital customer experience with a strong connection to a network of extraordinary stores that extends that seamless experience into the real world.


On its website and app, Saks offers an unparalleled selection of curated merchandise across fashion for women and men, beauty, jewelry, home décor and more. In addition to the shopping experience, customers come to Saks for inspiring editorial content, access to digital stylists, lifestyle experiences and other world-class services. The company is currently in the midst of a dramatic expansion, driven by significant enhancements to its platforms and offerings, with the goal of becoming the preeminent destination for luxury internationally.



Role Summary:

As an Analytics Engineer on the Data team that is tasked with driving the organization forward with Data, you will utilize your excellent technical skills to help us build a scalable Analytics Platform by understanding the questions our users are trying to answer and what outcomes they are trying to achieve. You will help deliver data solutions that address not only those questions but also additional needs.



Key Qualifications:

  • 5 + years experience as a data architect, data engineer, BI engineer or a similar role
  • SQL power user (Can write advanced SQL, interpret and optimize queries written by others)
  • Expert in at least one data warehouse modeling technique (e.g., Dimensional, bonus points for Data Vault)
  • Experience with data engineering tools for constructing and automating data pipelines and a clear understanding of the capabilities and limitations of various approaches/platforms preferably Snowflake, Airflow, dbt, Looker
  • Ability to drive business value through effective communication skills
  • Ability to collaborate with multiple stakeholders to ensure data capabilities
  • Experience with many of the following:
  • SQL / Python
  • CI / CD pipelines
  • Jenkins / GoCD / CircleCI
  • dbt / Informatica / Talend / Matilion
  • Snowflake / Google Big Query / Redshift
  • Passionate - about telling stories with data and teaching others to do it well



Role Description:

  • Create semantics and physical data models based on business needs that are agile, scalable and easy to understand
  • Write performant transformations
  • Help introduction and adoption of dbt
  • Assist with the data migration and decommission of legacy systems.
  • Help define best practices for data modeling, SQL query structure and optimization, dataops (e.g., version control, testing, CI/CD), and data compliance
  • Reconcile data issues and alerts between various systems, finding opportunities to drive improvements and automation
  • Work effectively in a fast-paced, dynamic environment
  • Mentor, and lead teams towards meeting business objectives
  • Extend support to keep the business running



Your Life and Career at Saks:

  • Be a part of an entrepreneurial team hyper focused on massive growth
  • Convenient and collaborative modern offices in Lower Manhattan with onsite perks
  • Benefits package for all eligible full-time employees (including medical, vision and dental)
  • An amazing employee discount


Thank you for your interest in Saks. We look forward to reviewing your application.


Saks provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Saks complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.


Saks welcomes all applicants for this position. Should you be individually selected to participate in an assessment or selection process, accommodations are available upon request in relation to the materials or processes to be used.

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