Senior Data Engineer, Fintech

Optasia is a fully enabled B2B2X financial technology platform covering scoring, financial decisioning, disbursement and collection. We are committed to enabling financial inclusion for all. We are changing the world our way.

We are seeking for enthusiastic professionals, with energy, who are results driven and have can-do attitude, who want to be part of a team of likeminded individuals who are delivering solutions in an innovative and exciting environment.

Data is at the core of Optasia’s growth plan, and the Data Engineering team is a significant contributor to our success, achieved through data-driven decision making and risk management. We leverage and ingest data from multiple sources into our large-scale data lakehouses, where data are processed in analytical pipelines. We develop and run the pipelines in a state-of-the-art open-source big data technology stack.

We are looking for a Senior Data Engineer to join our growing Data Engineering team. As part of our team, you will be able to enrich and further evolve the company’s big data infrastructure, and the highly scalable end-to-end batch and streaming data pipelines, contributing to Optasia’s success.

What you will do

• Provide technical expertise by improving scalability, stability, accuracy, speed and efficiency of our existing Data systems
• Design and develop end-to-end data processing pipelines
• Develop, maintain and optimize our core libraries for batch processing and ingestion of large volumes of data to the big data infrastructure
• Be comfortable navigating the following technology stack: Hadoop ecosystem, Hive, Scala, Spark, java, Python, scripting (Bash/Python), SQL etc.
• Design, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality
• Work closely with experienced Data Engineers, Solution Architects, ML engineers and System Administrators for the design, delivery and support of the company’s end-to-end data processing workflows
• Build and maintain CI/CD orchestration

What you will bring

• Bachelor’s or Master’s degree in Computer Science or Informatics.
• 5+ years of experience in Data Engineering.
• Strong hands-on expertise with the Apache Hadoop ecosystem (HDFS, Hive, Spark, YARN).
• Proficiency in Scala, Java, Python, SQL, scripting (Bash/Python).
• Experience with relational and NoSQL technologies.
• System administration skills in Linux.
• Practical experience with deployment, configuration, and maintenance of distributed systems and data/software engineering tools.
• Experience with CI/CD orchestration.

Optional requirements (will be considered a plus):

• Worked extensively in Hadoop / Spark / Spark Streaming / Hive.
• Experience with data and ML flow engines and tools, e.g. Apache Airflow, Apache NiFi, Druid.
• Hands-on exposure to modern data lake storage and table formats, e.g. Apache Iceberg, Apache Hudi.
• Experience in working with secure code development guidelines and coding practices (i.e. OWASP, NIST).
• Passion for learning new technologies and eagerness to collaborate with other creative minds.

Why you should apply

What we offer:

Competitive remuneration package

Extra day off on your birthday

Performance-based bonus scheme

Comprehensive private healthcare insurance

All the tech gear you need to work smart

Optasia’s Perks:

Be a part of a multicultural working environment

Meet a very unique and promising business and industry

Gain insights for tomorrow market’s foreground

A solid career path within our working family is ready for you

Continuous training and access to online training platforms

CSR activities and festive events within any possible occasion

Enjoy comfortable open space restaurant with varied meal options every day

Wellbeing activities access such as free on-site yoga classes, plus available squash court on our premises

In accordance with applicable pay transparency requirements, the salary range for this position will be communicated to candidates before the first step of the selection process, enabling informed discussions regarding the role.