Tech Lead Data Engineer
At a glance
Senior Data Engineering role at GFT Technologies. Kraków.
Pay not stated Lead Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build scalable data processing with Spark and Databricks, then extend pipelines using PySpark, Python and Java
- Create distributed systems designed for high availability and performance, including streaming with Kafka
- Design and tune cloud-native data solutions on Microsoft Azure
- Support CI/CD and DevOps work while collaborating with Agile teams on business requirements
- Trace complex technical flows, recommend solutions and help modernize applications and data platforms
What you bring
- At least seven years in software or data engineering
- Strong Spark and Databricks experience, with hands-on PySpark and strong Python skills
- Good Java development skills and deep knowledge of Microsoft Azure
- Experience with Kubernetes, Kafka streaming, CI/CD and DevOps practices
- A track record building distributed systems with high throughput and low latency
Who this fits
This senior technical role suits an experienced engineer who can independently tackle complex challenges and communicate with technical and business stakeholders. You’ll work in Agile teams and attend the client’s Kraków office three days each week.
From the employer
Type of contract: Employment contract
Salary range: 17400 - 26700 PLN gross
What will you do?
Join a strategic data transformation initiative focused on building and enhancing a large-scale data pipeline that feeds and reconciles inbound data from deal stores to consumer regulatory and settlement systems. You will work on modernizing enterprise-grade financial services platforms within a highly regulated environment, leveraging cloud-native technologies, big data solutions, and distributed streaming architectures. The role involves designing high-performance systems, improving data processing capabilities, and collaborating closely with technical and business stakeholders.
Your tasks
- Design and develop scalable data processing solutions using Spark and Databricks
- Build and enhance data pipelines using PySpark, Python and Java
- Develop high-performance, high-availability distributed systems
- Implement and maintain streaming solutions based on Kafka architectures
- Design and optimize cloud-native solutions in Microsoft Azure
- Support CI/CD processes and DevOps practices
- Collaborate with cross-functional Agile teams to deliver business requirements
- Analyze complex technical flows and propose suitable technical solutions
- Participate in system modernization and application transformation initiatives
- Ensure reliability, scalability and performance of data platforms
Your skills
- 7+ years of professional software engineering or data engineering experience
- Strong experience with Spark and Databricks
- Hands-on experience with PySpark
- Strong Python programming skills
- Good Java development experience
- Deep knowledge of Microsoft Azure cloud technologies
- Experience with Kubernetes
- Experience designing and implementing Kafka-based streaming solutions
- Experience with DevOps practices and CI/CD pipelines
- Experience building distributed, high-throughput and low-latency systems
- Strong problem-solving and analytical skills
- Ability to work independently on complex technical challenges
- Excellent communication and stakeholder management skills
- Experience working in Agile teams
Nice to have
- Experience providing Level 3 (DEV) production support in a high-pressure environment
We offer
- Hybrid work in our client's office (Kraków) 3 days a week
- Working in a highly experienced and dedicated team
- Benefit package tailored to your needs (medical, sport, lunch subsidy, life insurance, etc.)
- Online training and certifications
- Access to e-learning platform
- Social events
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