We are looking for a brilliant, quick-learner Data Engineer for our data engineering team - an independent logical thinker who understands the importance of data structuring for macro-business decisions.
The position combines high technical skills with business orientation, working closely with the analysts and the R&D team, and affecting the company's cross-departments decisions directly. Our Data Engineer should have the ability to speak in technical and practical terms, and more importantly, lead from one to the other, while dealing with challenges and creating them - to make our team even better than it is.
Roles and Responsibilities:
Creating and structuring end-to-end data pipelines & ETLs: from the source all the way to the analysts hands, enabling them the ideal conditions to make smart and data driven business decisions.
Cracking top industry data challenges while initiating and building creative technical solutions - in house Device Graph, Server-to-Server to multiple systems, Privacy challenges, Online-to-Offline and more.
Deep understanding of the business needs, technical requirements and the companys roadmap - and translating it into custom made data solutions and scalable products.
Craft code following best practices to ensure efficiency, while integrating CI/CD principles.
Writing multi-step scalable processes from more than 50 data sources - Marketing. Operations, CS, Product, CRM and more... tying them up to a valuable & useful source of insights for the analysts.
Understanding data challenges and weaknesses, and managing high standards monitoring and reliability processes.

We are seeking an experienced, data-driven and highly motivated BI Developer to join our data team. A strong candidate is an independent, analytically minded individual with strong data modeling and data engineering skills. Come and help us turn billions of daily events into critical information, business insights and graphical dashboards that will help to make impact decisions on our business
What you'll be doing:
Design, manage and maintain analytics products and BI solutions for the entire group
Work with a variety of relational and non-relational databases (Redshift, MySQL and others)
Develop ETL processes using different tools (Airflow, and others)
Design and develop data visualization (Tableau, redash and others)
Monitor the integrity and validity of the data reported.

We are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will play a pivotal role in our Data Engineering team, driving a multitude of responsibilities essential to fueling our groundbreaking R&D endeavors. Youll have the autonomy to explore and implement cutting-edge technologies and data solutions, collaborating with diverse team of data scientists, developers, analysts, and stakeholders. Every day will present new learning opportunities and challenges as we strive together to reshape the future of work.
Responsibilities:
Design, develop, and maintain scalable data pipelines and infrastructure to support the collection, processing, and analysis of large volumes of data.
Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to understand data requirements and develop solutions that meet business needs.
Implement best practices for data governance, security, and quality assurance to ensure the integrity and reliability of our data assets.
Optimize and tune existing data pipelines and processes for improved performance and efficiency.
Stay up to date with current best practices in the big data field.
Mentor and coach other members of the data engineering team, providing guidance and support to help them grow their skills and expertise.

Lead the design, implementation, and ongoing management of our company's data pipeline architecture.
Lead team architectural discussions
Manage a team of 2-3 data engineers
Work as an integral part of the data team and work closely with data Scientists, data Analysts and data Engineers.
Work directly with others (Developers, Product, and Internal stakeholders) to develop a solid understanding of the business application and requirements for which the application is being designed.

We are looking for a talented Data Practitioner to join our team and revolutionize the world of external data! In this role, you will be in charge of designing, implementing, testing, deploying, and maintaining our data products, which include data pipelines and ETL processes.
Additionally, you'll harness cutting-edge data science and engineering technologies, such as DBT, Databricks, and Large Language Models (LLMs), to create novel solutions that address complex business challenges.
This role demands strong technical skills alongside a deep understanding of various business contexts, making it ideal for someone passionate about employing the latest technologies to produce meaningful and impactful business outcomes.
Responsibilities:
Lead the development of data products, effectively translating business needs into actionable technical specifications.
Employ cutting-edge technologies including DBT, LLMs, and GenAI to push forward our data science and engineering practices.
Take charge of the entire data product lifecycle, from the creation to the maintenance of ETLs and real-time data pipelines.
Use data science tools to extract actionable insights and valuable business indicators from large datasets.
Ensure high reliability and performance of production systems through robust testing, monitoring, and alerting procedures.
Conduct data analysis across various sources, bringing valuable insights to products and catering to sectors like manufacturing, CPG, and SaaS.

Were a highly collaborative, friendly, inclusive and diverse group that prizes collaboration over competition. We provide opportunities to learn new skills, mentor fellow engineers, and contribute to the direction of both the team and the products for which were responsible. We work in a distributed, remote-friendly, high-trust environment where you manage your own time and have the flexibility to balance your work and personal life. As a remote employee, you connect to your co-workers mostly via Slack and Zoom. In this setting your ability to work unsupervised, communicate asynchronously, and take initiative in maintaining lines of communication is crucial.

What You'll Do:

Develop ETL jobs to gather data from multiple sources and provide insights into various product areas

Building data warehouses where large amounts of metrics and data will be stored

Interacting with many product groups within the organization to collect key metrics via APIs, Kafka integrations or direct data access

Participation in configuring and receiving uptime alerts related to the services you control.

Keeping services up and running in a healthy state.

MA?LYS is one of the fastest-growing global D2C startups with a self-built e-commerce platform that allows us to leverage data and optimize marketing funnels to bring clinically tested body care products to women worldwide. With years of rapid growth and millions of customers worldwide. MA?LYS is on track to become one of the biggest body care brands in the world. The company has built a strong tech backbone to leverage its data, collected over the span of dozens of million of $ in online advertising spend. The data analysis and predictive modeling guide the company’s decision making and play a central role in its success, creating a unique competitive edge over the industry and other e-commerce players. We are a team of people who want to make lasting, impactful changes, who live (and love) to see results, who innovate with passion, and who love a good sense of humor. Is our vibe your vibe? We are seeking a highly skilled Data Engineer to join its exceptional Data Team. You will play a crucial role in building the data foundations, which play an essential part in the company's growth engine.
Your life at MA?LYS will look like…
* Developing and maintaining scalable data pipelines and analytics infrastructure
* Build the infrastructure and processes required for optimal extraction, transformation and loading of data from a wide variety of data sources, using Python, Airflow, Rivery and BigQuery.
* Full responsibility for company & data department monitoring, logging and anomalies, support the Data scientists and data analyst’s requirements and needs
* Collaborate with varied teams and departments in order to deliver useful & insightful data products
You will thrive in this role if you have…
* 4+ years of relevant experience as a Data Engineer
* Strong knowledge of SQL.
* Strong knowledge of Python.
* Experience in managing and maintaining cloud resources
* Experience with BI tools (Tableau/Power BI/Looker/Sisense or similar)
* Experience with Data Warehouses
* Experience building ETLs
* Understanding business processes and collecting user requirements Advantages:
* Experience with Airflow
* Experience with GCP and streaming components
* Experience with Power BI

we are looking for a Senior Engineer with a data engineering background to join our growing ML Platform team. This is a great opportunity to enter the world of Machine Learning. Together well provide tools to develop more effective models, get them into production faster, and ensure that they continue to perform well over time.
What you will be doing:

Designing, building, and maintaining the ML infrastructure that allows models to make billions of real-time decisions every year.
Building a platform that enables managing a full ML model lifecycle - from researching to training, deploying, and serving predictions in real-time.
Building distributed data processing pipelines to support model development.
Acting as a consultant to researchers, data scientists, and expert analysts and enabling them to research new models faster and with greater precision by providing cutting-edge tooling.
Expanding our ML infrastructure to make it scalable, quick, and efficient to bring diverse models to production and to monitor their performance and drift over time.
Expanding the pool of internal customers able to use ML. Work with them to understand their needs and help them make the most of the infrastructure that well provide.
Acting as an advocate for MLOps, continually improving our processes, and raising our standards.

Required Experienced Software Engineer, Demand
What are some of the things you do on a day-to-day basis?
Develop one of the largest real time big data operation in the world to support over 40TB of new data every day
Have end to end ownership: Design, build, ship, measure and maintain our frontend and backend services
Collaborate with the brightest software engineers team members
Influence directly on the way billions of people discover the internet
Develop at unimaginable scale, serving hundreds of requests per second
Work on innovative projects that are the next growth engines for us
Here are some of the things software developers in our group did in the last several months:
A unique data pipeline for processing and managing user data signals
Develop a complete user identities graph and find deterministic and probabilistic methods to enrich it
An algorithmic model to predict the performance potential of a specific audience
Infrastructure to create unique audiences for advertisers based on various signals (behavioral, contextual, etc)
An A/B tests system to explore variations and experiments over audiences
Understand and use big data algorithms to estimate key business metrics over billions of impressions
Build user interface using React that serve thousands of users
And many more
Our Tech Stack:
Java, JS, TS, Python, React, Spark, Kafka, Hadoop, Cassandra, Vertica, ES, MySQL, Memcached, HDFS, BigQuery, Kusto, Docker, K8S, Linux, Prometheus, Grafana, Airflow.

Design, build, and launch data infrastructures that support multiple use cases across different products or domains.
Collaborate with engineers, product managers, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring and visualization.