Senior Data Engineer

Industry: Food & Beverage

Remote

Company size: 251-10K

Full-time

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Job description

A U.S.-based company, that is changing the way people consume dairy and revolutionizing vegan protein-rich products, is looking for a Senior Data Engineer. The selected engineer will collaborate with the data science and engineering team as well as provide technical leadership and utilize their expertise with cloud computing to design and deploy data engineering processes. The company is on a mission to change how people consume their food by making the process more transparent and ethical. This company has been successful in raising over $700 Million during their Series D round of funding.

Job Responsibilities:

Develop data pipelines, databases, and overall data lake architecture
Design and implement an analytical environment using third-party and in-house tools
Use Python to improve and automate analytics, ETL, and data quality platform
Build and deploy complex data models and model metadata
Create reports and dashboards
Take ownership of data dashboarding and presentation tools for the end users of our data products and systems
Conduct and support ingestion and migration of data in multiple types and formats
Partake in data retrieval, integration, and analysis
Understand data trends by analyzing collected data to establish facts
Deploy developed data solutions, user applications, databases, etc
Work closely with internal and third-party data producers, consumers, and users
Collaborate with non-technical stakeholders
Analyze, understand, and document existing workflows
Conduct integration and data structuring activities

Job Requirements:

Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
At least 8+ years of relevant experience as a Data Engineer
Experience with ETL, Data Modeling, and Data Architecture (at least 8-10 years)
Expertise in writing and optimizing SQL
Previous experience developing scripting software solutions using Linux/Unix
Operational experience in large data warehouses or data lakes
Demonstrable experience with AWS technologies, Databricks, Benchling, and Glue
Previous understanding of Lambda, and RDS (PostgreSQL, MySQL)
Expert-level skills in ETL optimization, designing, coding, and using Apache Spark or similar technologies to tune big data processes
Background developing applications and data pipelines to process and stream datasets at low latencies
Ability to track data - track data lineage, ensure data quality, and improve data discoverability
Sound understanding of distributed systems and data architecture (Lambda)
Ability to design and implement batch and stream data processing pipelines
Understanding of how to optimize the distribution, partitioning, and MPP of high-level data structures
Background in life science data a plus
Familiarity with Docker
Ability to clearly express ideas, listen, question, and share valuable information with colleagues
Effective presentation skills and the ability to communicate ideas to technical and non-technical audiences
Great to possess high energy and enthusiasm to boost productivity
Strong organization and planning skills, ability to establish a clear course of action to accomplish goals and objectives
Ability to effectively manage time and utilize resources and systems
Knowledge of task prioritization, ability to keep track of activities, and task completion
Self-starter with the know-how to work independently and multi-task while maintaining quality standards
Fluent in spoken and written English

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Prior experience using CI/CD (CircleCI, etc)
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