Data Architect

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.

• 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.

• 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.

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.

10 years +