DATA ENGINEER

Ready to grow your talent and make an impact? Join us and become part of a company that leads the digital transformation!​​

We are looking for a Data Engineer to join our new IT Platform & AI Team, who is eager to contribute to the design, implementation, and evolution of a scalable and governed Lakehouse platform.

The role involves building and operating modern data architectures on Databricks running on AWS, managing data ingestion, transformation, orchestration, and serving layers end to end. This is a high-ownership position for an experienced engineer who enjoys building robust data solutions while contributing to engineering standards, team growth, and technical excellence.

ABOUT US:
Namirial supports its customers in their digital transformation journey by providing trusted digital transaction management solutions. Namirial’s digital trust services include solutions for customer onboarding, agreement automation, signature workflow orchestration, identification, multi-factor authentication, electronic signatures, electronic registered delivery, long-term archiving, and electronic invoicing.
Founded in 2000 in Italy, Namirial Group is now present in more than 85 countries and employs over 1400 people. With its international network of more than 170 strategic partners, Namirial serves over three million customers worldwide and processes several million transactions per day. Namirial is accredited as a Qualified Trust Service Provider under the European Regulation 910/2014 eIDAS.

YOUR NEW KEY RESPONSIBILITY:

• Design and implement end-to-end data architectures on a Databricks Lakehouse Platform following Medallion architecture principles (Bronze, Silver, Gold layers)
• Build and operate scalable ETL/ELT pipelines for batch and streaming workloads using PySpark, Spark SQL, and Spark Structured Streaming
• Develop and manage Databricks infrastructure, including Delta Lake tables, Databricks SQL, and Lakeflow Jobs
• Implement data governance, lineage, and access control using Unity Catalog, ensuring security-by-design and audit readiness
• Define and implement data quality checks, monitoring, logging, and observability practices across the data ecosystem
• Establish engineering best practices around coding standards, testing, CI/CD, and Infrastructure as Code
• Collaborate with analytics, machine learning, security, and engineering teams to enable reliable and efficient data-driven solutions
• Contribute to team growth through collaboration, knowledge sharing, and technical guidance
• Support the continuous improvement of platform reliability and scalability

YOU MAY BE A FIT FOR THIS ROLE IF YOU HAVE:
Hard Skills

• 5+ years of experience as a Data Engineer in complex enterprise environments
• Hands-on experience designing and operating data platforms from the ground up
• Strong experience with Databricks Lakehouse Platform, including Delta Lake and Unity Catalog
• Solid working knowledge of AWS cloud services and cloud-based data architectures
• Strong proficiency in Python, SQL, and Apache Spark (PySpark / Spark SQL)
• Experience developing and operating both batch and streaming pipelines, including Spark Structured Streaming
• Experience with orchestration solutions such as Databricks Lakeflow Jobs and/or external orchestrators (Airflow, Prefect, Dagster, AWS Step Functions)
• Solid understanding of data modeling techniques, including dimensional modeling and Lakehouse modeling approaches
• Understanding of data governance, data quality, security-by-design principles, and compliance requirements
• Experience working with common data formats such as Parquet, Delta, Avro, and JSON
• Knowledge of streaming technologies such as Kafka or Amazon Kinesis
• Familiarity with Infrastructure as Code practices, including Terraform (Databricks provider), CloudFormation, and/or Databricks Asset Bundles
• Experience with CI/CD pipelines using tools such as GitLab CI, Jenkins, or similar solutions
• Good command of English, both written and spoken

Soft Skills

• Strong analytical and problem-solving skills
• Ownership mindset and ability to work independently in a high-responsibility environment
• Team-oriented approach with strong collaboration skills across technical functions
• Ability to communicate technical concepts clearly and effectively
• Proactive attitude focused on reliability, scalability, and continuous improvement

Nice to Have

• Databricks certifications such as Databricks Certified Data Engineer Associate or Professional
• Hands-on experience with dbt
• Advanced experience with Databricks ecosystem components such as Lakeflow Declarative Pipelines, Auto Loader, and Lakeflow Connect
• Experience mentoring engineers or leading a small technical team
• Experience with Databricks performance tuning and cost optimization, including cluster sizing, SQL Warehouse optimization, Photon, and partitioning strategies
• Experience working in regulated environments with GDPR, compliance, or audit requirements

COMPENSATION PACKAGE:

• Employment Classification: Employee under B2 the CCNL Metalmeccanica Industria
• Fixed Salary (RAL): €50.000 – €55.000 gross per year, depending on the assessed level of autonomy and responsibility
• Meal vouchers: €7 for each day worked on-site

• Working in an exciting and innovative market environment ​

• Flexible working hours, uncomplicated holiday planning and home office ​

• Dynamic and open-minded working atmosphere with attractive benefits ​

• An international and motivated team that welcomes YOU!​

RECRUITMENT PROCESS:

• HR Discovery Call (30 minutes – in English)
  Initial conversation with HR to explore your background, motivation, and overall fit.
• Interview with the Direct Leader
  In-depth discussion focused on your experience, key skills, and alignment with team and business goals.
• Technical Deep Dive / Business Case
  Practical session to assess role-relevant skills, problem-solving approach, and business acumen.
• Assessment+ Feedback Session (1 hour)
  Online assessment focused on personality traits and motivational drivers, followed by a dedicated feedback discussion.
• Reference Check