Senior Data Engineer – Technical Intelligence

Input Output (IOHK)

full-time

Posted on: 9/23/2025

Origin: • 🇬🇧 United Kingdom

✨ AI Apply

Senior

AirflowAmazon RedshiftApacheAWSETLPySparkPythonSparkSQLTerraform

About the role

Own and drive the end-to-end data process for intelligence (business and technical) across all company ventures, including acquiring, processing (ETL), modeling with AI/ML, and reporting.
Contribute to an automated process that leverages a data warehouse alongside ML/AI on AWS to generate insights.
Serve as the competitive positioning expert in the blockchain landscape, providing data insights to fulfill stakeholder requirements.
Architect and build performant and scalable data engineering pipelines using AWS; drive data system design, modeling, data quality, and delivery.
Work with senior leadership and stakeholders to understand data value, define key metrics for competitive positioning, and gather requirements.
Collaborate with data engineers, analysts, data scientists, ML and AI engineers to operationalize models and integrate LLM-related logic into data pipelines.
Provide direct exposure to strategic decision-making, analysing company strategy and new venture planning from a quantitative perspective.
Use Scrum methodologies to drive prioritization, planning, and execution of tasks for the data intelligence team.

A MSc/PhD in Computer Science, AI, or a related field is a strong plus.
Typically 7+ years of professional experience in data engineering or data science.
Expertise in data modeling and data warehousing, including building and optimizing data schemas and data lakes.
Hands-on experience specifically with AWS data services like Glue, Redshift, S3, Lambda, Athena.
Advanced proficiency in Python, SQL, PySpark.
Hands-on experience with big data frameworks like Apache Spark, DBT, workflow orchestration tools like Apache Airflow or AWS Step Functions, and Infrastructure-as-Code like CloudFormation or Terraform.
Hands-on experience with MLOps in operationalizing machine learning models in production.
Experience leading and mentoring data engineers and driving data system projects from conception to completion.
Solid critical thinking, research, and problem-solving skills, with the ability to quickly grasp any data-related domain.
Solid foundation of large-scale data systems, including data warehousing and data processing, including parallel processing, data partitioning, cost efficiency.
Solid data programming covering algorithms, data structures, design patterns, and relational databases.
Solid software development practices, version control, testing, and CI/CD.
Knowledge of Machine Learning (ML), Natural Language Processing (NLP), or Deep Learning (DL).
Knowledge of the Blockchain domain and passionate about gaining further breadth and depth of the domain.