Overview
We are looking for an experienced and strategic Senior Data Architect to lead the design, modernization, and governance of enterprise-scale data platforms and architectures. The ideal candidate will have strong expertise in data engineering, cloud data ecosystems, enterprise integration, analytics, AI/ML data readiness, and modern data governance practices.
The role requires close collaboration with business stakeholders, enterprise architects, AI teams, engineering teams, and leadership to build scalable, secure, and high-performing data solutions that support digital transformation and advanced analytics initiatives.
Responsibilities
- Define and implement enterprise-wide data architecture strategies, standards, and best practices.
- Design scalable data platforms, data lakes, data warehouses, and modern lakehouse architectures.
- Lead architecture discussions for cloud-based data ecosystems across AWS, Azure, or GCP.
- Design end-to-end data pipelines for structured, semi-structured, and unstructured data.
- Establish data governance, metadata management, lineage, security, and compliance frameworks.
- Work closely with AI/ML teams to enable high-quality data foundations for analytics and AI solutions.
- Define enterprise data models, master data management (MDM), and data integration strategies.
- Guide teams on ETL/ELT frameworks, streaming architectures, and real-time data processing.
- Collaborate with business stakeholders to translate business requirements into scalable technical solutions.
- Lead performance optimization, scalability planning, and cost optimization initiatives for data platforms.
- Evaluate and recommend new tools, technologies, and accelerators in the data and AI ecosystem.
- Provide technical leadership and mentoring to data engineers, developers, and architects.
- Ensure compliance with enterprise security, privacy, and regulatory requirements.
- Participate in solution estimation, proposal creation, architecture reviews, and customer discussions.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or related field.
- Cloud certifications preferred:
- AWS Certified Data Analytics
- Azure Data Engineer / Solutions Architect
- Google Professional Data Engineer
- TOGAF or enterprise architecture certifications are an added advantage.
Essential skills
Technical Skills
- Strong experience in enterprise data architecture and large-scale data platform implementation.
- Expertise in cloud platforms such as:
- AWS (Redshift, Glue, EMR, Athena, S3)
- Azure (Azure Data Factory, Synapse, Databricks, ADLS)
- GCP (BigQuery, Dataflow, Dataproc)
- Strong knowledge of:
- Data Warehousing
- Data Lakes / Lakehouse Architecture
- ETL / ELT frameworks
- Data Modeling
- Data Governance
- Master Data Management
- Metadata Management
- Experience with modern data engineering tools such as:
- Databricks
- Snowflake
- Kafka
- Spark
- Airflow
- dbt
- Strong SQL and database design expertise.
- Understanding of AI/ML data pipelines and analytics ecosystems.
- Experience with API integrations and enterprise integration patterns.
- Familiarity with DevOps/DataOps/MLOps practices.
Leadership & Functional Skills
- Strong stakeholder management and communication skills.
- Experience leading distributed/global teams.
- Strong problem-solving and strategic thinking capabilities.
- Experience working in Agile delivery environments.
- Ability to drive architecture governance and technical decision-making.
Experience
10 years +