We build. We create impact.

We are seeking  a Senior Data Engineer to support the growth of the company and building our data analytics SaaS platform for the retail industry, particularly in the context of the increasing diversity of volumes, sources, and types of data utilized by the organization.

We work on solutions that:

• Handle large volumes of diverse data from IoT/event streams, computer vision, transactional, operational, and supply chain sources
• Enrich AI and Computer Vision capabilities with a business intelligence layer, transforming data into actionable insights for retailers

Your Role

As a member of Memory's Data Team, your role will involve ensuring the optimal use of data within the Memory analytics platforms. Your primary responsibilities will include:

• Design, build and manage our data pipelines, ensuring  data is seamlessly integrated into our data lakehouse.
• Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.
• Work collaboratively with various teams, including, Data Science, Infrastructure,  Software, Product, Consulting to understand their data needs and provide solutions.
• Implement robust and fault-tolerant systems for data ingestion and processing.
• Participate in data architecture, engineering and data management decisions, bringing your strong experience and knowledge to bear.
• Ensure the security, integrity, and compliance/quality of data according to industry and company standards.
• Preparing the data specifications for collection from our partner distributors and assisting with the data aspects of implementing Memory analytics platforms.
• Conducting an assessment and continuous improvement of data models, which already integrates multiple types of data from various sources (structured and unstructured data).

Qualifications we’re looking for.

• At least 8 years of engineering experience related to Data Engineering/Data Ops.
• Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
• Experience with distributed processing technologies and frameworks, such as Spark/Databricks and distributed storage systems (e.g., HDFS ...).
• Solid understanding of Spark and ability to write, debug and optimize Spark code.
• Expertise with any orchestrator such as Airflow, Dagster, Prefect or similar frameworks.
• Knowledge of Data Lakehouse architectures or OLAP/Cube systems for advanced analytics.
• Familiarity with Docker & Kubernetes.
• Knowledge of Kafka, Event Hubs, Pub/Sub is a plus.
• Knowledge of dbt, cube.dev is a plus.
• A deep understanding of best practices in data architecture, data management, security, and compliance.
• Team spirit and excellent communication skills to collaborate with cross-functional teams.

By joining our team, you’ll have the opportunity to work on exciting projects in the retail sector, learn, and grow in a dynamic environment.