Senior Data Engineer

CNTXT, Inc.; Abu Dhabi; On-site; AED 300,000 - 460,000; Full time

Job summary

CNTXT, Inc. in Abu Dhabi is seeking a hands-on Senior Data Engineer to design and build the foundational data layer for a growing data platform.

You will integrate data from multiple sources, including structured, semi-structured, and unstructured data, and design scalable data models that create a trusted view of our data for internal reporting and analytics. This role sits at the intersection of data engineering, architecture, modeling, and analytics.

Qualifications

• 5+ years of experience in Data Engineering, Architecture, or Data Modeling.
• Strong SQL skills and ability to work with large, complex datasets.
• Experience with ETL/ELT patterns and data pipelines.
• Experience with cloud data platforms and data warehouses/lakehouses.
• Ability to design scalable data models and architectures.
• Understanding of metadata management, data cataloguing, lineage, taxonomy, and governance.

Responsibilities

• Design scalable data architectures and canonical data models that consolidate information across systems.
• Ingest data from multiple platforms, APIs, databases, files, and other sources.
• Develop reliable ETL/ELT pipelines and transformation frameworks.
• Build a data catalogue and metadata structures for data assets.
• Enable analytics teams to build dashboards and reporting on top of trusted datasets.

Skills

5+ years experience

Strong SQL

Cloud data platforms

ETL/ELT patterns

Data modeling

Data governance

Job description

We are looking for a hands-on Senior Data Engineer with strong data architecture and modeling expertise to design and build the foundational data layer for a growing data platform.

About the Role

We are looking for a hands‑on Senior Data Engineer with strong data architecture and modeling expertise to design and build the foundational data layer for a growing data platform. You will be responsible for bringing together data from multiple platforms and sources, including structured, semi-structured, and unstructured data, and designing scalable data models that create a consistent and trusted view of our data. This role sits at the intersection of data engineering, architecture, modeling, and analytics. You will work closely with engineering, data, product, and business teams to establish a scalable data foundation that initially powers internal reporting and analytics and evolves to support data products and external-facing use cases.

What You'll Do

Data Architecture & Modeling

• Design scalable data architectures and canonical data models that consolidate information across multiple systems and data sources.
• Define entities, relationships, taxonomies, metadata, and schemas that establish a consistent representation of data across the organization.
• Build a robust single source of truth that can evolve as new data sources, products, and use cases are introduced.
• Make architectural decisions around data storage, transformation, access patterns, lineage, and governance.

Data Integration & Engineering

• Design and build pipelines to ingest data from multiple platforms, APIs, databases, files, and other sources.
• Work with structured and unstructured datasets, transforming heterogeneous inputs into standardized and usable data models.
• Develop reliable ETL/ELT pipelines and transformation frameworks.
• Design systems that can scale as data volume, variety, and number of sources increase.
• Implement data validation, monitoring, lineage, and quality controls.

Catalogue & Metadata

• Develop the underlying data structures required to maintain a comprehensive and searchable catalogue of data assets.
• Define metadata standards, classifications, relationships, and identifiers across different data sources.
• Establish mechanisms for identifying duplicates, inconsistencies, and relationships across datasets.
• Design the architecture with future catalogue and marketplace capabilities in mind.

Analytics & Reporting

• Build curated data layers and datasets that enable reliable reporting and analytics.
• Enable analytics teams to build dashboards and reporting on top of trusted, well‑defined datasets.
• Define key metrics and ensure consistent definitions across reporting use cases.

What We're Looking For

• 5+ years of experience in Data Engineering, Data Architecture, or Data Modeling.
• Strong experience designing relational, dimensional, and/or domain-oriented data models.
• Demonstrated experience designing scalable database and data platform architectures.
• Strong SQL skills and hands-on experience working with large and complex datasets.
• Experience integrating data from multiple heterogeneous sources, including APIs, databases, files, and unstructured or semi-structured sources.
• Strong understanding of ETL/ELT patterns, data pipelines, schema design, and data transformation.
• Experience with modern cloud data platforms and data warehouses/lakehouses.
• Understanding of metadata management, data cataloguing, lineage, taxonomy, and data governance.
• Experience designing data layers that support BI, analytics, and downstream applications.
• Ability to move between high-level architecture and hands-on implementation.

Nice to Have

• Experience building data catalogues, metadata platforms, master data systems, or marketplace-style data products.
• Experience with data lakehouse architectures and modern data stacks.
• Experience modeling highly heterogeneous or unstructured datasets.
• Experience with semantic layers, knowledge graphs, entity resolution, or ontology design.
• Experience designing data platforms that serve both internal analytics and external-facing products.
• Familiarity with AI/ML datasets and data management workflows.

What Success Looks Like

You will create a scalable data foundation where information from multiple systems can be consistently represented, discovered, trusted, and consumed. The architecture you build will enable teams to move from fragmented data sources toward a unified catalogue and reliable source of truth, while providing the foundation for future data products.