Senior Data Engineer

Senior Data Architect

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.