Offer summary

Qualifications:

Degree in Computer Science or related field, 2-5+ years of data engineering experience, Experience with AWS/Snowflake or Google Cloud, Proficient in Python for ETL processes, Strong understanding of relational databases.

Key responsabilities:

Ensure accuracy and quality of data

Manage ETL data flow and scripting

Integrate data from various sources

Transform data into relational models

Optimize and maintain data processes

Job description

Data Engineer (part-time)

About Us

Avea is a Swiss longevity startup with the vision to become the leading player in the evidence-based longevity supplement industry. We offer science-based longevity supplements to target multiple hallmarks of ageing, allowing individuals to improve their well-being by slowing down ageing itself. Our mission is to optimise people’s health- and lifespan, helping them keep or regain their vitality to live as healthily as possible for as long as possible.

The Role

As a Data Engineer you will be responsible for ensuring that we as an organisation can leverage data effectively. In essence, you bridge the gap between raw data and actionable insights, making them a crucial asset in data-driven decision-making.

It is initially a part-time role that can convert into full-time opportunity. Depending on the location we offer B2B or EOR contract.

This is fully remote role.

Duties and responsibilities

Data Quality and Consolidation:

Data Quality: Ensure the accuracy, completeness, and consistency of data across various systems.
Data Flow Management: Oversee the flow of data from extraction to transformation and loading (ETL) into the appropriate data stores.
Data Consolidation: Integrate data from different sources like Snowflake and Google Cloud to create unified, accurate datasets.

ETL Process Development (Python):

Develop Python Scripts for ETL: Write and maintain Python scripts to extract, transform, and load (ETL) data from various sources.
Automate ETL Pipelines: Automate the data transformation and loading processes to ensure real-time or scheduled data availability.
Data Transformation: Convert transactional data into relational models (e.g., customer and order tables) to make it usable for analytics.

Data Extraction:

Connect to Data Sources: Build and manage Python connections to platforms like Snowflake and Google Cloud.
Data Download and Loading: Extract raw data, clean it, and load it into relevant environments for processing.

Data Transformation:

Relational Data Modeling: Transform extracted data into a structured, relational format (e.g., customers, orders, order details, shipments, inventory).
Preprocessing for Analysis: Ensure that data is ready to be used without the need for further pivoting or transformation by end users.

Independence and Scalability:

Data Pipeline Independence: Work towards making the data pipelines and transformation processes more independent and scalable.
Maintain and Optimize: Regularly maintain and optimize the data processes to ensure efficiency.

Requirements:

Experience & Qualifications:

Degree in Computer Science, Data Engineering, or a related field (or equivalent work experience).
2-5+ years of experience in data engineering, ETL processes, or a similar role.
Experience working with AWS/Snowflake or Google Cloud/PosgreSQL
Experience in writing Python scripts to connect with databases or cloud environments (e.g., Snowflake, Google Cloud).

Experience with designing, building, and maintaining ETL pipelines using Python and other relevant tools.
Strong understanding of transforming transactional data into relational formats (e.g., customers, orders, inventory).
Experience managing and organising the flow of data between systems to ensure quality and accuracy.
Strong understanding of relational database concepts (tables, keys, relationships) and experience in transforming data into a relational structure.

Skills & Competencies

Self-direct: Taking initiative and ownership of one’s actions and outcomes
Problem-Solving: Exceptional problem-solving skills, with the ability to diagnose bottlenecks in the customer journey and creatively resolve them.
Communication: Proactive and timely communication

Why join us

We believe that the best companies help you live your life the way you want and become the person you want to be. That's why we focus on promoting your personal freedom and growth. As a member of our team, you'll enjoy:

Working at a well-funded, early-stage startup in the longevity industry.
Being part of a dynamic, high-performing, and fun team.
A high degree of personal responsibility, creative freedom, and opportunities.
Collaborating with the brightest researchers in the longevity field and with successful and renowned serial
entrepreneurs.
Fully remote opportunities with home office/coworking support.
A strong team culture with regular team events and off-sites.
Join us as we shape the emerging longevity space, fostering healthier, longer lives!