What this position is all about
The incumbent will primarily focus on building and maintaining optimized and highly available data pipelines that facilitate Data Science modelling, deeper analysis within marketing analytics. He/she will be responsible for building data processing frameworks that handle the business’s growing data needs. He/she works with data science as well as reporting teams in leveraging data with data mining, modeling, and production. He/she strives to continuously develop new and improved data engineering capabilities. This is an Individual contributor role reporting to Sr Manager, Marketing Analytics.
Who You Are
- Build data pipelines that transform raw, unstructured data into formats data scientists & the Analytics community can use for analysis. Be responsible for creating and maintaining the analytics infrastructure that enables almost every other data function
- Create and maintain optimal data pipeline architecture
- Data wrangling - Assemble large, complex data sets that meet business requirements
- Identify, design, and implement internal process improvements
- Optimize data delivery and re-design infrastructure for greater scalability
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using cloud infrastructures like Snowflake and AWS technologies
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
- Work with internal and external stakeholders to assist with data-related technical issues and support data infrastructure needs
- Prior experience implementation of complex machine learning models and scaling them up to production
- Strong programming skills in Python, PySpark and SQL
- Strategic Thinking – Think strategically by clearly anticipating future trends and consequences. Create clear and compelling business plan and communicate effectively to cross-functional partners.
- Drive for Results - Pushes self and others to exceed goals and achieve breakthrough results. Recognizes the key actions necessary to achieve results, establishes and communicates the priorities to supervisor, demonstrates persistence in removing barriers to achieving results, and encourages others to do the same.
- Business Acumen - Leverages business judgment to shape strategy, based on understanding of operational, financial, and organizational requirements and capabilities.
You also Have:
- Have had at least 5-8 years of working experience working in a data engineering domain, preferably as a Data Engineer in a fast-paced environment and complex business setting.
- To demonstrate an ability translate algorithms provided by data science team and implement those in as well as strong knowledge in Linux, OS tools, and file-system level troubleshooting. He/she must have substantial experience working with big data infrastructure tools such as Python, Amazon SQS, and Redshift. A suitable candidate will also be proficient in PySpark, Spark Streaming, AWS, and EMR.
- Experience working on a cloud data platform is a plus (Snowflake preferred)
- Demonstrated experience in building and maintaining reliable and scalable ETL on cloud based big data platforms as well as experience working with varied forms of data infrastructure inclusive of relational databases
- Must also have had experience in data warehousing inclusive of dimensional modeling concepts and demonstrate proficiency in scripting languages
- Demonstrate machine learning experience and experience with big data infrastructure inclusive of MapReduce, Hive, HDFS, YARN, HBase, etc.
- 4-6 years structuring databases and manipulating large data sets
- 4+ years writing code in relevant languages (e.g. Python / PySpark, SQL, Java or Scala)
- Bachelor's degree required; preferably in Engineering, Mathematics, Statistics or Computer Science
- Master's preferred
As a full stack Data Engineer, You will:
- Identify use cases to engineer data into Snowflake environment; Create automated data pipelines to feed structured, clean data from multiple data sources into Snowflake
- Ensure single source of truth in data
- Understand business needs to define data models/algorithm needs; generating insights from complex data questions
- Develop scalable machine learning solutions and deploy in production
- Work collaboratively with other team members to define the advanced analytical modeling capabilities and outcomes required to enable use cases in Merchandising and Supply chain
- Work collaboratively with the other Analysts, Data Scientists, and Data Architects to identify and spec the data fields and data features needed for analytical models, and adapting and testing them
- Design the test and learn / measurement approaches and techniques for newly deployed use cases
- Work with Data team and Systems Specialists to operationalize models to scale use cases
- Work with other members of the team including Data, Analytics, and Product teams to peer review code, write unit tests, and provide feedback on data structuring and modeling approaches + scalability as required
Your Life and Career at Saks Fifth Avenue:
- Be part of a world-class team; work with an adventurous spirit; think and act like an owner- operator!
- Gain access to state of the art modern tech stack that includes Snowflake, AWS Suite, Python/PySpark, Airflow, MicroStrategy, Tableau, etc.
- Exposure to rewarding career advancement opportunities, from IT to Human Resources, Merchandising to Finance.
- A culture that promotes a healthy, fulfilling work/life balance.
Thank you for your interest with HBC. We look forward to reviewing your application.
HBC 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, HBC 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.
HBC 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.