Sr. Data Engineer

Perfect Day

330

Berkeley, CA, United States

Posted on: 2022-05-04

Category: food

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Expired

Employment type:

Full time

Experience required:

Senior

Salary

Salary not provided

About the company:

At Perfect Day, we believe in empowering people to enjoy the dairy foods they love - products full of delicious taste and luscious texture - while making the world a kinder, greener place.

We make milk protein that is nutritionally identical to protein from cow's milk, but made using flora fermentation instead of animals. We're working with food and dairy companies to deliver high-quality protein and products that are delicious, nourishing, sustainable, and humane.

It's #KinderGreenerDairy for people, planet, and animals - without the compromise.

It's a Perfect Day to change the world! At Perfect Day, we're doing just that.

Perfect Day was founded in 2014 to create delicious, nutritious dairy products that everyone can love. We’re using fermentation (not animals) to make dairy proteins that are the foundation for foods like ice cream, cheese and yogurt – all with the distinctive taste and textures that consumers demand, but without lactose or environmental downsides. Through partnerships with respected brands, we’re working to launch a whole range of dairy products that will help shape a humane, sustainable food system for future generations.

Perfect Day is looking for a Sr Data Engineer to join the Data Science and Engineering team to assist in developing data pipelines, databases, and the overall data lake architecture. The Successful Candidate will provide technical leadership and apply their knowledge of cloud computing (AWS) to design and implement data engineering processes. This role will report to Sr. Director, Data Science and Engineering.

It's a Perfect Day to change the world. The day when delicious dairy goodness is something everyone can love. The day we say goodbye to the downsides of factory farming. The day we throw a big party with luscious, animal-free milk, cheese, yogurt, and ice cream, all made with Perfect Day! We hope you join us!

Essential functions:

Responsible for designing and implementing an analytical environment using third-party and in-house tools and using Python, Scala, or Java to automate the ETL, analytics, and data quality platform from the ground up.

Design and implement complex data models, model metadata, build reports and dashboards, and own data presentation and dashboarding tools for the end users of our data products and systems.

Work with leading edge technologies like Redshift, EMR, Lambda and more

Competencies:

Communication Skills - Ability to express ideas clearly, listening skills, questioning skills, sharing of information with colleagues and presentation skills

Energy and Enthusiasm – Consistently maintaining a high level of energy, enthusiasm and productivity

Planning and Organizing – Establishing a clear course of action to accomplish goals and objectives

Time management skills- effective use of resources and systems, ability to prioritize activities, completion of tasks

Required education and experience:

This position requires a Bachelor's Degree in Computer Science or a related technical field, and 5+ years of relevant employment experience

5+ years of work experience with ETL, Data Modeling, and Data Architecture.

Expert-level skills in writing and optimizing SQL.

Experience with AWS technologies Glue, Lambda, RDS ( PostgreSQL, MySQL) etc..

Solid Linux skills.

Experience operating very large data warehouses or data lakes.

Preferred experience:

Expertise in ETL optimization, designing, coding, and tuning big data processes using Apache Spark or similar technologies.

Experience with building data pipelines and applications to stream and process datasets at low latencies.

Show efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data.

Sound knowledge of distributed systems and data architecture (lambda)- design and implement batch and stream data processing pipelines, knows how to optimize the distribution, partitioning, and MPP of high-level data structures.

Experience with life sciences data a plus.

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