Data Engineer

At Epignosis our mission is simple yet bold: To make learning technologies accessible to every business, regardless of geography, sector, or company size. And we’ve been doing just that for more than two decades, empowering millions of people to grow, learn, and thrive through technology that’s both powerful and affordable. 

We're rapidly becoming one of Greece's largest SaaS companies, serving 12,000+ companies and 11+ million learners worldwide with solutions like TalentLMS (an award-winning cloud LMS built for simplicity), eFront (an enterprise LMS), TalentCards (a mobile app for deskless training), and TalentHR (a lightweight HRIS for people operations). 

Our success is built on a team that believes that work should matter — not only to you, but to the world around you. We're looking for people who light up when solving hard problems, who care deeply about their craft, and who want to build something that genuinely helps people grow.

We are searching for a skilled Data Engineer to join our Data Team and play a key role in implementing our Data Transformation project. The ideal candidate will design, develop, and maintain scalable data pipelines and workflows to support analytics and business intelligence initiatives. Additionally, they will be responsible for managing data infrastructure, optimizing databases and schemas, and ensuring data integrity.

This role involves close collaboration with Developers, DevOps, AI Engineers and other cross-functional teams to optimize queries and databases, propose scalable architecture solutions, and identify data requirements that drive our services forward.

As a Data Engineer, you will:

• →Monitor and optimize database performance, implementing tuning measures while ensuring data integrity and security.
• →Provide proactive and reactive data management support, including user training and troubleshooting.
• →Work closely with developers to optimize queries and design efficient database schemas.
• →Collaborate with AI Team to support AI-driven initiatives.
• →Design, develop, and maintain ETL pipelines to efficiently process and integrate data from multiple sources.
• →Partner with different team within the Engineering department to understand data needs and deliver data solutions.
• →Implement data modeling techniques to create efficient schemas for relational and non-relational databases, such as Aurora, DynamoDB or other.
• →Optimize data workflows and storage solutions to enhance performance and scalability.
• →Ensure data quality and consistency through validation and cleaning processes.

To be successful in this role as a Data Engineer, you should have:

• 3+ years of experience in data engineering or similar roles.
• Proficiency in Python and experience with Apache Spark for large-scale data processing.
• Proficiency in SQL and hands-on experience with database management systems.
• Experience with cloud technologies, particularly AWS (e.g., S3, Glue, Lambda).
• Strong understanding of databases, data lakes, and data warehousing principles.
• Experience with NoSQL databases (e.g., MongoDB, DynamoDB).
• Strong data modeling skills to support analytical and reporting needs.
• Experience in designing and optimizing ETL/ELT pipelines.
• Familiarity with data warehousing solutions and BI tools (e.g., Tableau, Power BI, QuickSight).
• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Strong analytical and problem-solving abilities.
• Multi-constrained optimization considering performance, cost, value, complexity, ease of maintenance and tradeoffs thereof.
• Excellent communication and teamwork skills.
• Ability to work in a fast-paced environment and manage multiple priorities.

• Experience with big data technologies (e.g., Hadoop, Kafka).
• Familiarity with AWS Athena and Redshift will be a plus.