APEX – Data Engineer

Fa Errt Saasfaprod1 Open · verified Oct 24, 2026

Bucuresti - Ilfov, Romania Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Fa Errt Saasfaprod1. Bucuresti - Ilfov, Romania.

Pay not stated Data Engineering salary

RoleData Engineering

SeniorityMid-level

LocationBucuresti - Ilfov, Romania

PostedSep 1, 2026 · 7w ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build and maintain Databricks pipelines that ingest, transform and deliver large datasets through ETL and ELT processes
Shape Delta Lake models and storage, then add checks for data quality, reconciliation and platform monitoring
Tune Spark workloads to improve performance and cost efficiency, and resolve pipeline reliability or consistency problems
Connect Databricks workloads with Java and Spring Boot services using REST APIs and event-driven patterns
Create reusable Python libraries, support CI/CD automation, and take part in design reviews and production investigations

What you bring

At least seven years working in data or software engineering
Strong hands-on ability with Databricks, Spark or PySpark, Python and SQL
A record of designing enterprise data pipelines and working with Delta Lake, data modeling and data quality
Experience connecting data platforms to Java or Spring Boot services, plus knowledge of REST APIs and microservices
Practical use of Git and CI/CD, alongside familiarity with data governance and metadata management

Who this fits

This role suits a mid-level data engineer comfortable owning pipeline development, production support and technical design discussions. You’ll collaborate with backend teams and colleagues across distributed, multicultural groups. The work also calls for openness to using AI tools and agents, including within Databricks.

From the employer

Job Summary

We are seeking a highly skilled Senior Data Engineer to join the APEX engineering team and contribute to the design, development, and evolution of our next-generation data platform.

The successful candidate will play a key role in building scalable and reliable data pipelines on Databricks, leveraging PySpark and Python to process large-scale datasets and support critical business processes. The role requires close collaboration with Backend Engineering teams to integrate data services with a Java-based ecosystem through APIs and microservices.

Data Platform Development:

Design, develop, and maintain enterprise-grade data pipelines using PySpark on different systems as Databricks.
Build efficient ETL/ELT processes for large-scale data ingestion, transformation, and delivery.
Design and optimize Delta Lake data models and storage structures.
Implement data quality controls, reconciliation mechanisms, and monitoring solutions.
Analyze and optimize Spark workloads for performance and cost efficiency.

Backend Integration:

Develop integrations between Databricks workloads and Java/Spring Boot applications.
Design and consume REST APIs for data exchange between platform components.
Support event-driven and service-oriented architectures.
Collaborate with backend teams to ensure end-to-end data flow reliability and scalability.

Software Engineering Excellence:

Develop reusable Python frameworks and libraries to standardize data processing.
Apply software engineering best practices including clean code, testing, code reviews, and documentation.
Contribute to CI/CD implementation and deployment automation.
Participate in architecture reviews and technical design discussions.
Strong Adoption of AI tools, AI agents and Agentic AI to bring more efficiency to deliver value. Usage of AI within databricks. Proactively propose news usage / AI tools on our technical environment being open minded.

Operational Excellence:

Ensure reliability, observability, and supportability of production pipelines.
Investigate and resolve performance, stability, and data consistency issues.
Participate in production support and root cause analysis activities.
Implement monitoring and alerting mechanisms across the data platform.

Leadership & Collaboration:

Collaborate with architects, product owners, business analysts, and development teams.
Contribute to technical roadmaps and platform modernization initiatives.

Technical Skills:

7+ years of experience in Data Engineering or Software Engineering.
Strong expertise in:
- Databricks
- Apache Spark / PySpark
- Python
- SQL
Proven experience designing and implementing enterprise data pipelines.
Strong understanding of:
- Delta Lake
- Data Modeling
- Data Quality
- Metadata Management
- Data Governance
Experience integrating data platforms with Java/Spring Boot applications.
Solid knowledge of REST APIs and Microservices architectures.
Experience with Git and CI/CD practices.