Staff Engineer, Merchandising Data Engineering

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming, Statistics, Biostatistics

Job Description

#ITEC770417

Albertsons Companies is one of the largest food and drug retailers with 2,300+ stores. The Albertsons Companies family of brands includes some of the most prominent brands in food retailing, with a growing base of loyal shoppers. Thanks to the professionalism, diversity, spirit, and friendliness of our people, we have locations across the U.S.

The Enterprise Data & Analytics team at Albertsons Companies is looking for an experienced Data Engineer to work for one of the most transformational food and drug retailers in the United States. Albertsons operates over 2,300 stores under 19 well-known banners including Albertsons, Safeway, Vons, Jewel-Osco, Shaw's, Acme, Tom Thumb, Randalls, United Supermarkets, Pavilions, Star Market, Haggen and Carrs. The company reported revenue of over $60 billion from over 34 million weekly shoppers and is the third largest private company in the country.

The Enterprise Data & Analytics Department has an opening for a Staff Engineer, Merchandising Data Engineering. This position is located in Pleasanton, California.

Position Purpose

The Enterprise Data & Analytics team at Albertsons inspires to build best in class customer experiences and revolutionize the food and drug retail industry. We are looking for people who are excited in re-imagining the grocery experience by harnessing the power of AI and digital technologies. The Data Engineering team uses a decoupled and near real time data integration paradigm to make data available to improve pricing, promotions management, assortment planning, vendor negotiations, store operations etc. to proactively improve product lifecycle.

You will be responsible for designing, developing, testing and managing large scale, high-performance data processing systems (batch and/or streaming) in a Multi Cloud environment to provide a robust analytical pipeline. The candidate will have a background in computer science or a related technical field with experiences working with high volume, message-based data integration technologies. A successful candidate will be both technically strong and business savvy, with a passion to make an impact through creative storytelling and timely actions. You are a self-starter, smart yet humble, with a bias for action.

Key Responsibilities include, but are not limited to:

• Lead, architect, design and develop secure, scalable, high-performance and reliable and cost-effective Big Data platform software and services in a Multi-Cloud environment
• Provide technical leadership in Data Engineering practices. Partner with architecture, Infosec, and development teams across the entire enterprise to establish a strong relationship and trust for prioritizing and delivering projects on time and with a high degree of quality.
• Establish patterns for re-use, standards and best practices for Data Engineering & Analytics such that data timeliness and quality are maximized.
• Partner with the Audit, Compliance and Governance leaders to ensure data is secured and conforms to the guidelines laid out by the organization and the industry.
• Partner with cross-functional teams to deliver large scale strategic projects as well as ongoing operational activities related to Big Data Platform. Interface with cross functional leaders and represent point of views to drive measurable success.
• Drive meetings and lead discussions. Prioritize projects across the team and allocate resources to meet business and team goals.

Qualifications:

• Bachelor's or Master's in computer engineering, computer science or related area.
• 7+ years proven experience in developing and deploying data pipelines, preferably in the Cloud; Azure and Snowflake experience is a plus.
• 2+ years of proven expertise in creating pipelines for real time and near real time integration.
• 2+ years of proven experience with Spark SQL, Spark Streaming and using Core Spark API to explore Spark features to build data pipelines.
• 1+ years of experience with at least one programming language like Python, Java or Scala
• 2+ years of hands-on experience in productionizing and deploying Big Data platforms and applications. Hands-on experience working with: Relational/SQL, distributed columnar data stores/NoSQL databases (MongoDB or Cassandra), graph databases, timeseries databases, HDFS, HBase, Map Reduce, NiFi, Spark streaming, Kafka, Sqoop, Hive, Oozie, Avro, and more
• Databricks and Delta table knowledge is a plus.
• Extensive experience in data transformations for Merchandising business use cases will be a plus.
• Knowledge for handling exceptions and automated re-processing and reconciling
• Passion for Data Quality with an ability to integrate these capabilities into the deliverables.
• Prior use of Big Data components and the ability to rationalize and align their fit for a business case.
• Experience in working with different data sources - flat files, XML, JSON, Avro files and databases.
• Proficiency in techniques for slowly changing dimensions.
• Knowledge of Jenkins for continuous integration and End-to-End automation for application build and deployments.
• Ability to integrate into a project team environment and contribute to project planning activities.
• Experience in developing implementation plans and schedules and preparing documentation for the jobs according to the business requirements.
• Lead ambiguous and complex situations to clear measurable plans.
• Proven experience and ability to work with people across the organization and skilled at managing cross-functional relationships and communicating with leadership across multiple organizations.
• Proven capabilities for strong written and oral communication skill with the ability to synthesize, simplify and explain complex problems to different audiences.