Data Engineer, DaaS

PayPay; Poland; Hybrid; PLN 90,000 - 120,000; Full time

Job summary

A leading FinTech company in Poland seeks an experienced Data Engineer to create and manage data ingestion pipelines. Applicants should have a minimum of 7 years' experience and hands-on skills with Databricks, Snowflake, and Scala. This role offers a hybrid workstyle and includes numerous benefits such as annual leave and social insurance.

Benefits

Annual leave up to 14 days

Personal leave

Social Insurance

Qualifications

• Minimum 7 years as a Data Engineer or in a similar role.
• Hands-on experience with leading technologies required.
• Strong communication and collaboration skills.

Responsibilities

• Create and manage data ingestion pipelines.
• Develop workflows using Databricks and Spark.
• Collaborate across teams to facilitate data flow.

Skills

Data Engineering

Scala

Python

SQL

Databricks

Snowflake

Delta Lake

Spark

Airflow

Terraform

Job description

PayPay is a FinTech company that has grown to over 70M users since its launch in 2018. Our team is hugely diverse with members from over 50 different countries.

OUR VISION IS UNLIMITED

We dare to believe that we do not need a clear vision to create a future beyond our imagination. PayPay will always stay true to our roots and realize a vision that no one else can imagine by constantly taking risks and challenging ourselves.

We are looking for people who can embrace this challenge, refresh the product at breakneck speed and promote PayPay with professionalism and passion.

Job Description

PayPay's rapid growth necessitates the expansion of its product teams and underscores the critical need for a resilient Data Engineering Platform. This platform is vital to support our increasing business demands.

The Data Pipeline team is tasked with creating, deploying, and managing this platform, utilizing leading technologies like Databricks, Delta Lake, Spark, Scala, and the AWS suite. We are actively seeking skilled Data Engineers to join our team and contribute to scaling our platform across the organization.

Main Responsibilities

• Create and manage robust data ingestion pipelines leveraging Databricks, Airflow, Kafka, and Terraform.
• Ensure high performance, reliability, and efficiency by optimizing large-scale data pipelines.
• Develop data processing workflows using Databricks, Snowflake, Delta Lake, and Spark technologies.
• Maintain and improve the Data Lakehouse, utilizing Unity Catalog for efficient data management and discovery.
• Construct automation, frameworks, and enhanced tools to streamline data engineering workflows.
• Collaborate across teams to facilitate smooth data flow and integration.
• Enforce best practices in observability, data governance, security, and regulatory compliance.

Qualifications

• Minimum 7 years as a Data Engineer or similar role.
• Hands-on experience with Databricks, Snowflake, Delta Lake, Spark, and Scala.
• Proven ability to design, build, and operate Data Lakes or Data Warehouses.
• Proficiency with Data Orchestration tools (Airflow, Dagster, Prefect).
• Familiarity with Change Data Capture tools (Canal, Debezium, Maxwell).
• Strong command of at least one primary language (Scala, Python, etc.) and SQL.
• Experience with data catalog and metadata management (Unity Catalog, Lakeformation).
• Experience in Infrastructure as Code (IaC) using Terraform.
• Excellent problem-solving and debugging abilities for complex data challenges.
• Strong communication and collaboration skills.
• Capability to make informed decisions, learn quickly, and consider complex technical contexts.
• Hybrid Workstyle (flexible working style including Remote and office)
• In principle, 9:00am-5:45pm + 1h break (actual working hours: 7h45m + 1h break)

Holidays and Benefits

Every Sat/Sun/National holidays (In Japan)/New Year's break/Company-designated Special days

• Annual leave (up to 14 days in the first year, granted proportionally according to the month of employment.
• Personal leave (5 days each year, granted proportionally according to the month of employment)
• Annual salary paid in 12 installments (monthly)
• Based on skills, experience, and abilities
• Reviewed once a year
• Special Incentive once a year *Based on company performance and individual contribution and evaluation
• Late overtime allowance
• Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)