Data Engineer, Grouper Technology
Management system for quality assurance
Open for applications
Management system for quality assurance
1-20 employees
Open for applications
1-20 employees
Company mission
To deliver strategic technology consultancy with precision, scale and heart.
Role
Who you are
- Data Dynamo! Are you ready to immerse yourself in a role that demands technical mastery and strategic insight?
- Educational Qualification: Hold a third level degree in a related discipline such as Computer Science, Statistics, or Data Analytics, demonstrating a strong foundation in relevant knowledge areas
- Programming Proficiency: Possess a proficient working knowledge of Python and/or Scala, coupled with hands-on coding skills, reflecting a commitment to software engineering excellence
- Technical Expertise: Bring experience in Software Engineering to the table, with a solid understanding of Apache Spark and related Big Data stacks and technologies, enabling effective development within complex data environments
- Problem-Solving Prowess: Demonstrate the ability to debug complex data issues within extensive datasets containing billions of records, showcasing your analytical acumen and attention to detail
- Code Quality Advocate: Exhibit a strong desire to write clean and efficient code, consistently striving for excellence rather than settling for "good enough."
- SQL Proficiency: Possess a working knowledge of SQL, facilitating effective data manipulation and analysis tasks
- DevOps and Git Competence: Understand DevOps tools and the Git workflow, contributing to collaborative and efficient development processes
- Project Lifecycle Experience: Have direct experience with the entire data project lifecycle, from requirements gathering through to design, implementation, evaluation, and presentation of results, demonstrating your capability to deliver end-to-end solutions
Desirable
- Cloud Services Savvy: Demonstrate hands-on experience with cloud services such as Azure Databricks, IBM Public Cloud, Google Cloud, and AWS, showcasing your ability to leverage cloud infrastructure for advanced data analytics
- ️Data Science Tool Proficiency: Possess a working knowledge of Data Science tool chains and stacks, including Jupyter and R, enabling you to conduct sophisticated data analysis and modelling tasks
- Big Data Technology Mastery: Exhibit in-depth knowledge of Big Data technologies such as Hadoop, Cassandra, Kafka, Redis, Hive, and Impala, providing you with a solid foundation for managing large-scale data processing
- Machine Learning Expertise: Understand Machine Learning algorithms and have experience in running ML models at scale, contributing to data-driven insights and decision-making processes
- Data Manipulation Proficiency: Showcase experience in data partitioning, transformation, and in-memory computations, particularly in handling large-scale join/group-by/aggregations tasks efficiently
- Spark Application and Pipeline Design: Demonstrate proficiency in designing and building Spark applications and data pipelines, along with expertise in monitoring and optimizing Spark job performance for enhanced efficiency
- Customer-Centric Approach: Showcase experience in gathering customer requirements and presenting KPI reporting and data science project outputs, ensuring alignment with client needs and objectives
What the job involves
- We're on the lookout for a Data Engineer to join our Enterprise Architecture Team
- As part of our dynamic team, you'll collaborate closely with skilled professionals from various technical backgrounds to deliver cutting-edge, data privacy-compliant analytics insights
- Business Objective Translation: Understand customer business objectives and adeptly translate them into actionable data analytics code
- Software Engineering Excellence: Apply best-practices in Software Engineering to craft robust Big Data analytics applications that effectively deliver value to our clients
- Automation Advocate: Champion the adoption of automation, particularly in the realm of automated quality checks within existing data products, aiming to streamline processes and enhance efficiency
- Collaborative Enhancement: Collaborate closely with members of the Data Science and Privacy Risk teams to strengthen and meticulously document data privacy checks, ensuring robust compliance measures are in place
- ️Best Practice Implementation: Implement and uphold best practices in data management, software testing within a Big Data context, software maintenance, and information security, fostering a culture of excellence and reliability
- This role offers remote flexibility, welcoming candidates from across Europe
Our take
HR workflows are often tedious and difficult to manage. Without a centralised platform, these inefficiencies take time away from pressing business needs. Grouper offers a solution to this through the creation of an innovation management system that facilitates quality assurance in line with governance risk and compliance.
The company's platform differs from competitors in that it's designed for maximum flexibility, meaning that it can be moulded to the specific needs of each business. Further, by offering a product that is easily integrated into existing methodology, Grouper is able to provide its solution with minimal disruption to existing processes.
Major clients already include Aer Lingus and Crown Roofing. Through its 2021 round of seed funding, Grouper has focused on employee expansion and investing in the continual development of its management platform to secure more deals with leading companies.
Steph
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
May 2024
$1m
SERIES A
Sep 2021
$0.6m
SEED
Total funding: $2.1m
Company HQ
Dublin, Ireland
Leadership
Mojtaba Akbari
(Founder & Executive Director)Previously the Head of IT at The K Club and CTO at Sepam. Since founding Grouper, Akbari has taken on a number of advisory roles for companies including Actavo, Vhi, and Aer Lingus.
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