01 Zakres zadań

Working hours

12:00 PM – 8:00 PM (CEST)

Responsibilities

Build a FinOps Data Platform – design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data to produce a cloud cost chargeback dataset.
Develop robust ETL (Extract, Transform, Load) processes to integrate data from diverse sources into our data ecosystem.
Implement data validation and quality checks to ensure accuracy and consistency.
Design and maintain data models, schemas, and database structures to support analytical and operational use cases.
Optimize data storage and retrieval mechanisms for performance and scalability.
Evaluate and implement data storage solutions, including relational databases, NoSQL databases, data lakes, and cloud storage services.
Build and maintain integrations with internal and external data sources and APIs.
Implement APIs and web services for data access and consumption.
Ensure compatibility and interoperability between different systems and platforms.
Ability to build reliable, observable data workflows.
Knowledge with cloud platform (Azure data factory, Synapse, AWS S3, BiqQuery, etc.)
Scheduling, dependencies, retries, backfills and data validation.

02 Wymagania

9 must-have · 1 język

Must-have

Python

Zaawansowany

SQL

Zaawansowany

Data integration (incl. SEI integration)

Zaawansowany

Data modeling

Zaawansowany

Power BI

Zaawansowany

Cloud (AWS /Azure / GCP)

Zaawansowany

Data orchestration tools

Zaawansowany

Kafka

Zaawansowany

Hadoop

Zaawansowany

Wymagane języki

Angielski

Zaawansowany

03 Profil kandydata

Requirements

Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
Proven experience in data engineering, software development, or related roles.
Proficiency in programming languages is commonly used in data engineering (e.g., Python, Java, Scala, etc.).
Strong knowledge of database systems, data modeling techniques, and SQL proficiency.
Proficiency with ETL tools commonly used in data engineering (e.g., Databricks, Azure Data Factory).
Experience with big data technologies and frameworks (e.g., Hadoop, Spark, Kafka, etc.).
Familiarity with cloud platforms and services (e.g., AWS, Azure, GCP, Snowflake, etc.).
Excellent problem-solving skills and attention to detail.
Experience with Cloudability Data Platform a plus
6-8 years’ experience

04 Benefity

Pakiet medyczny

05 O firmie

PTT Consulting

<50 · Warszawa

Data Engineer will work for a global leader in gaming, who deliver entertaining and responsible gaming experiences for players across all channels and regulated segments, from Gaming Machines and Lotteries to Sports Betting and Digital. Leveraging a wealth of compelling content, substantial investment in innovation, player insights, operational expertise, and leading-edge technology, company’s solutions deliver unrivaled gaming experiences that engage players and drive growth. The company has a well-established local presence and relationships with governments and regulators in more than 100 countries around the world, creating value by adhering to the highest standards of service, integrity, and responsibility.

Zobacz ogłoszenia Profil firmy Strona www