Company Description Wiser Solutions is a suite of in-store and eCommerce intelligence and execution tools. We're on a mission to enable brands, retailers, and retail channel partners to gather intelligence and automate actions to optimize in-store and online pricing, marketing, and operations initiatives. Our Commerce Execution Suite is available globally. Job Description When looking to buy a product, whether it is in a brick and mortar store or online, it can be hard enough to find one that not only has the characteristics you are looking for but is also at a price that you are willing to pay. It can also be especially frustrating when you finally find one, but it is out of stock. Likewise, brands and retailers can have a difficult time getting the visibility they need to ensure you have the most seamless experience as possible in selecting their product. We at Wiser believe that shoppers should have this seamless experience, and we want to do that by providing the brands and retailers the visibility they need to make that belief a reality. Our goal is to solve a messy problem elegantly and cost effectively. Our job is to collect, categorize, and analyze lots of structured and semi-structured data from lots of different places every day (whether it’s 20 million+ products from 500+ websites or data collected from over 300,000 brick and mortar stores across the country). We help our customers be more competitive by discovering interesting patterns in this data they can use to their advantage, while being uniquely positioned to be able to do this across both online and instore. We are looking for a lead-level software engineer to lead the charge on a team of like-minded individuals responsible for developing the data architecture that powers our data collection process and analytics platform. If you have a passion for optimization, scaling, and integration challenges, this may be the role for you. What You Will Do Think like our customers – you will work with product and engineering leaders to define data solutions that support customers’ business practices. Design/develop/extend our data pipeline services and architecture to implement your solutions – you will be collaborating on some of the most important and complex parts of our system that form the foundation for the business value our organization provides Foster team growth – provide mentorship to both junior team members and evangelizing expertise to those on others. Improve the quality of our solutions – help to build enduring trust within our organization and amongst our customers by ensuring high quality standards of the data we manage Own your work – you will take responsibility to shepherd your projects from idea through delivery into production Bring new ideas to the table – some of our best innovations originate within the team Technologies We Use Languages: SQL, Python Infrastructure: AWS, Docker, Kubernetes, Apache Airflow, Apache Spark, Apache Kafka, Terraform Databases: Snowflake, Trino/Starburst, Redshift, MongoDB, Postgres, MySQL Others: Tableau (as a business intelligence solution) Qualifications Bachelors/Master’s degree in Computer Science or relevant technical degree 10+ years of professional software engineering experience Strong proficiency with data languages such as Python and SQL Strong proficiency working with data processing technologies such as Spark, Flink, and Airflow Strong proficiency working of RDMS/NoSQL/Big Data solutions (Postgres, MongoDB, Snowflake, etc.) Solid understanding of streaming solutions such as Kafka, Pulsar, Kinesis/Firehose, etc. Hands-on experience with Docker, Kubernetes, infrastructure as code using Terraform, and Kubernetes package management with Helm charts Solid understanding of ETL/ELT and OLTP/OLAP concepts Solid understanding of columnar/row-oriented data structures (e.g. Parquet, ORC, Avro, etc.) Solid understanding of Apache Iceberg, or other open table formats Proven ability to transform raw unstructured/semi-structured data into structured data in accordance to business requirements Solid understanding of AWS, Linux and infrastructure concepts Proven ability to diagnose and address data abnormalities in systems Proven ability to learn quickly, make pragmatic decisions, and adapt to changing business needs Experience building data warehouses using conformed dimensional models Experience building data lakes and/or leveraging data lake solutions (e.g. Trino, Dremio, Druid, etc.) Experience working with business intelligence solutions (e.g. Tableau, etc.) Experience working with ML/Agentic AI pipelines (e.g. , Langchain, LlamaIndex, etc.) Understands Domain Driven Design concepts and accompanying Microservice Architecture Passion for data, analytics, or machine learning. Focus on value: shipping software that matters to the company and the customer Bonus Points Experience working with vector databases Experience working within a retail or ecommerce environment. Proficiency in other programming languages such as Scala, Java, Golang, etc. Experience working with Apache Arrow and/or other in-memory columnar data technologies Supervisory Responsibility Provide mentorship to team members on adopted patterns and best practices. Organize and lead agile ceremonies such as daily stand-ups, planning, etc Additional Information EEO STATEMENT Wiser Solutions, Inc. is an Equal Opportunity Employer and prohibits Discrimination, Harassment, and Retaliation of any kind. Wiser Solutions, Inc. is committed to the principle of equal employment opportunity for all employees and applicants, providing a work environment free of discrimination, harassment, and retaliation. All employment decisions at Wiser Solutions, Inc. are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, national origin, family or parental status, disability, genetics, age, sexual orientation, veteran status, or any other status protected by the state, federal, or local law. Wiser Solutions, Inc. will not tolerate discrimination, harassment, or retaliation based on any of these characteristics. Show more Show less
