Lead Data Engineer
- Posted 2 months ago
- Be among the first 10 applicants
Job Description
Job Description
As Lead Data Engineer, you will help architect, build and run the data platform that supports reporting, analytics, and self-service BI across the GAC Group. A key part of the role is ensuring that our data pipelines are reliable, monitored, tested, and easy to support. We use Databricks, DBT, and Airflow through Astronomer, and need someone who can help us strengthen how we build, operate, and maintain production data flows.
You will work with business stakeholders, analysts, architects, and engineers to turn business needs into reusable and trusted data products. Beyond central reporting, you will also help develop a broader platform where teams can work with their own data in a governed, secure, scalable, and reliable way.
We are looking for someone with strong data engineering skills, a practical operational mindset, and the ability to guide others in building data solutions that work well in production.
Job Requirements
Educational Qualification:
Degree in Computer Science, Engineering or similar knowledge.
Master's degree in computer science, Information Systems or related field.
Professional Qualification
Cloud certifications.
Databricks, data build tools, airflow, astronomer, general tech and data certifications.
Specialist Knowledge
Data Factory, Python, Git, Databricks.
SQL Server.
Power BI includes data modelling and DAX development.
Azure Platform.
Linux OS Concepts.
Airflow.
Data Modelling – KIMBAL Concepts, ETL Knowledge.
Communication Skills
Communicate effectively across all levels, engaging and inspiring at senior levels internally and externally.
Cultural awareness within a multi-cultural corporate environment.
Good English Spoken Language Skills Are Essential.
Adaptability to new tools, logical reasoning and problem solving.
Experience Level
5+ years of related working experience.
As Lead Data Engineer, you will help architect, build and run the data platform that supports reporting, analytics, and self-service BI across the GAC Group. A key part of the role is ensuring that our data pipelines are reliable, monitored, tested, and easy to support. We use Databricks, DBT, and Airflow through Astronomer, and need someone who can help us strengthen how we build, operate, and maintain production data flows.
You will work with business stakeholders, analysts, architects, and engineers to turn business needs into reusable and trusted data products. Beyond central reporting, you will also help develop a broader platform where teams can work with their own data in a governed, secure, scalable, and reliable way.
We are looking for someone with strong data engineering skills, a practical operational mindset, and the ability to guide others in building data solutions that work well in production.
Job Requirements
Educational Qualification:
Degree in Computer Science, Engineering or similar knowledge.
Master's degree in computer science, Information Systems or related field.
Professional Qualification
Cloud certifications.
Databricks, data build tools, airflow, astronomer, general tech and data certifications.
Specialist Knowledge
Data Factory, Python, Git, Databricks.
SQL Server.
Power BI includes data modelling and DAX development.
Azure Platform.
Linux OS Concepts.
Airflow.
Data Modelling – KIMBAL Concepts, ETL Knowledge.
Communication Skills
Communicate effectively across all levels, engaging and inspiring at senior levels internally and externally.
Cultural awareness within a multi-cultural corporate environment.
Good English Spoken Language Skills Are Essential.
Adaptability to new tools, logical reasoning and problem solving.
Experience Level
5+ years of related working experience.
More Info
Key Skills
Linux OS Concepts
Azure Platform
ETL Knowledge
About Company
Skills:
data engineering , data warehouses , snowflake , Data Lineage, Data Security, Data Modelling, Etl Development, Informatica, Sql, Encryption, Data Governance, master reference data, data integration patterns, Regulatory Compliance, Relational Databases, reconciliation frameworks, access controls, data quality controls, cloud-based data platforms, metadata, error handling, audit trails
Skills:
Azure Data Factory, Pyspark, Databricks, Cloud native tools
Skills:
DVC (Data Version Control), Power Bi, Tableau, Sql, Tensorflow, Numpy, Pytorch, Pandas, Python, Data Visualization, Data Cleansing, Scikit-learn, Jupyter, Azure ML labelling services, Data Analysis, NoSQL databases, Feature engineering, Diversity sampling, GCP Vertex AI, AWS SageMaker, Large-scale data annotation workflows, Weak Supervision labelling functions, Uncertainty sampling, Active Learning strategies
Skills:
Cloud Computing, Machine Learning, Data Visualization, Big Data, Python, Sql, Statistical Analysis, Deep Learning