Principal Technology Consultant – Data Architect
Lead enterprise data architecture and shape the future of data-driven…
Job Purpose
Lead the design and delivery of scalable, secure, and high-performing enterprise data architectures, ensuring robust data governance, quality, integration, and modern data platform solutions that enable data-driven decision-making.
KEY RESPONSIBILITIES
- Define and maintain the enterprise data architecture strategy (cloud, hybrid, on-premises).
- Design data platforms (Data Lake, Data Warehouse, Lakehouse) and integration patterns.
- Establish data engineering standards and best practices (ETL/ELT, streaming, transformation).
- Define enterprise data quality framework and governance model.
- Design data cleansing, standardisation, and master data management strategies.
- Define and oversee data migration architecture and strategy for legacy system modernisation.
- Establish data modeling standards (conceptual, logical, physical models).
- Define data validation, monitoring, and quality scorecards.
- Ensure data lineage, traceability, and auditability across systems.
- Select and govern data technologies and platforms (AWS, GCP, Oracle, etc.).
- Optimize performance, scalability, and cost efficiency of data platforms.
- Define data governance, metadata, and catalog strategies.
- Provide technical leadership and guidance to Data Engineers and other teams.
- Collaborate with business and IT stakeholders to align data architecture with business goals.
- Carry out such acts as shall be required for the proper fulfilling of duties listed above.
QUALIFICATIONS & EXPERIENCE
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or equivalent.
- 7 to 10+ years in Data Engineering, BI, or Architecture roles
- Minimum 3–5 years in a Data Architect or senior design role
- Strong experience in data migration and legacy modernization projects
TECHNICAL SKILLS
- Strong expertise in enterprise data architecture design (Data Lake, Data Warehouse, Lakehouse).
- Advanced knowledge of data modeling methodologies
- Deep understanding of ETL/ELT architecture and data integration patterns (batch, streaming, API-based).
- Strong experience with cloud data platforms, including one or more of:
- AWS (S3, Glue, Redshift, EMR, Kinesis, DMS)
- GCP (BigQuery, Dataflow, Dataproc, Pub/Sub)
- Oracle OCI (Autonomous Data Warehouse, GoldenGate, Data Integration)
- Expertise in data migration strategies and tools, especially for legacy systems (e.g., Oracle databases).
- Strong knowledge of data governance frameworks, including data quality, metadata, and lineage management.
- Experience designing data quality frameworks, including validation rules, profiling, and monitoring.
- Knowledge of data cleansing and standardisation strategies at enterprise level.
- Familiarity with big data and distributed processing frameworks (Apache Spark, Kafka).
- Experience with data catalog and governance tools (e.g., Glue Catalog, Dataplex, Oracle Data Catalog).
- Strong understanding of performance optimization techniques (partitioning, indexing, query tuning).
- Knowledge of security and access control mechanisms for data platforms.
- Familiarity with modern data stack tools (Airflow, dbt, Delta Lake, Iceberg).
COMPETENCIES
- Strong problem-solving and analytical skills
- Excellent communication and stakeholder management skills, with the ability to translate business needs into technical solutions.
- Strong leadership and mentoring abilities to guide Data Engineers and technical teams
- Ability to work under pressure and meet deadlines
- Adaptability and willingness to learn new technologies
- Customer-focused mindset
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The SIL Team is a group of IT professionals with expertise in delivering high-quality software solutions to clients worldwide. They specialize in working with businesses in Mauritius, India, and Africa, and have a deep understanding of the unique needs of these regions.