Founded by Mastercard and IBM in 2018, Trūata is a fast-moving tech start-up headquartered in Dublin, Ireland. Trūata engineers privacy-enhancing products and solutions that help major organizations to leverage the value of data while meeting the highest standards of personal data protection set out by the GDPR and other leading global regulations. Following our rapid growth in Europe over the last three years, we have expanded from our flagship anonymization service to offer a portfolio of software and SaaS solutions.
Trūata is recruiting for a permanent Data Engineer to join our Customer Success Team in Dublin, Ireland. You will be a member of a highly skilled, cross-disciplinary technical team delivering data privacy-compliant analytics insights in close collaboration with your peers and external client stakeholders. This is an excellent opportunity for someone to grow their Big Data analytics skills and apply them to real-world problems.
As an employer, Truata is fully supportive of a flexible working environment.
What you will do
- Understand customer business objectives and translate those into data analytics code
- Apply Software Engineering best-practices to build Big Data analytics applications that deliver value to our clients
- Drive and increase adoption of automation, particularly automated quality checks in existing data products
- Collaborate with members of the Data Science and Privacy Risk teams to further boost and document robust data privacy checks
- Implement best practices for data management, SW testing in a Big Data context, SW maintenance, and information security
What you need:
- Third level degree in a related discipline, e. g. Computer Science, Statistics, Data Analytics
- Good working knowledge of Python and / or Scala
- Experience in Software Engineering and strong, hands-on coding skills
- Knowledge of Apache Spark and related Big Data stacks / technologies
- Ability to debug complex data issues while working on very large data sets with billions of records
- A strong desire to write code cleanly and efficiently and never be satisfied with just attaining a “good enough”.
- Working knowledge of SQL
- Understanding of DevOps tools and Git workflow
- Direct experience with the entire data project lifecycle, including requirements gathering, design, implementation, evaluation and presentation of results
What is also good to have
- Hands-on experience with cloud services, e.g., Azure Databricks, IBM Public Cloud, Google Cloud, AWS
- Working knowledge of Data Science tool chains and stacks, such as Jupyter, R
- In-depth knowledge of Big Data technologies including Hadoop, Cassandra, Kafka, Redis, Hive, Impala
- Understanding of Machine Learning algorithms and how to run ML at scale
- Experience with data partitions, transformation, and in-memory computations (large-scale join / group-by / aggregations)
- Experience with designing and building Spark applications and data pipelines, monitoring and optimizing Spark job performance
- Customer requirements gathering and KPI reporting / presentation of data science project output
We take pride in offering an energetic and contemporary employee experience, supported by and array of benefits that provide our employees and their families with flexibility, quality and value. These include excellent health insurance, contributory pension scheme and free lunches!