Data Engineer

PlanetArt•Calabasas, CA

3h•$92,000 - $100,000•Hybrid

About The Position

PlanetArt’s vision is to be the leading seller of personalized and make-on-demand products worldwide. We provide consumers with unmatched tools and content and an unparalleled end-to-end customer experience that result in high-quality, meaningful finished products and memorable celebrations of live events. The company’s brands include the popular FreePrints and FreePrints Photobooks apps and the industry leading SimplytoImpress card and stationery site, as well as Personal Creations, CafePress and ISeeMe! Visit www.planetart.com to learn more about our brands. We have more than 500 team members across multiple offices, primarily in Calabasas CA, San Diego CA, Woodridge IL, Minneapolis, MN and Pleasanton, CA. We also have team members in two company-owned offices in China, as well as in Europe. PlanetArt is looking for a Data Engineer to support the company’s Forecasting & Pricing Group. This role is responsible for ETL of data from production systems into data warehouse for Data Science projects. PLEASE NOTE: Candidates much be local to or willing to relocate to the Calabasas area as we operate on a hybrid work model (3 days onsite, 2 remote)

Requirements

3+ years of data engineering experience designing and developing large data pipelines using Apache Kafka, Apache Spark, and workflow management tools (Airflow) required.
2+ years of experience with data warehousing and data lake management including Amazon Redshift, and AWS S3 data lakes required.
2+ years of experience working with cloud-based services like AWS Glue, serverless computing with AWS Lambda, and using Airflow on AWS required.
3+ years of experience using analytic SQL, working with traditional relational databases and/or distributed systems (Amazon S3, Redshift, MySQL, SQLServer), required.
3+ years of experience programming languages (e.g. Python, Pyspark, Spark) required.
2+ years of experience of data visualization with Tableau and PowerBI dashboards and reports required.
Strong understanding of data modeling principles including Dimensional modeling, data normalization principles.
Ability to independently perform performance optimization and troubleshooting for data pipelines and ML deployments.
Strong communication skills – written and verbal presentations.
Excellent conceptual and analytical reasoning competencies.
Comfortable working in a fast-paced and highly collaborative environment.
Familiarity with Agile Scrum principles and Atlassian software (Jira, Confluence).

Responsibilities

Creating data pipelines using extract, transform and load processes to streamline and manage data from different sources and make it understandable, accessible and usable.
Optimizing database systems for performance and integrating types of databases, warehouses and analytical systems.
Implementing algorithms for data transformation and use and machine learning models to make data useful.
Partner with cross-functional teams (Data Science, Sales, Finance, Supply Chain, Marketing, Operations) particularly to align forecasts with strategic and operational planning.
Identify key risks and opportunities within forecast assumptions and present recommendations to leadership.
Monitor deployed forecast model performance, track variances, and continuously refine methodologies.
Troubleshooting data-related issues by identifying the main cause and fixing common issues in data pipelines.
Design and deliver recurring reports, dashboards, and presentations for senior leadership.
Mentor and provide guidance to junior analysts on best practices in analytics.