Enterprise Data Architect

Company Description Aptus Data Labs is a leading Data and AI company specializing in Pharma, Manufacturing & Supply Chain, Banking & FinTech, and Technology domains. We offer innovative analytical solutions and consulting services to help businesses make quick, data-driven decisions essential for growth and sustainability in evolving industries. Leveraging cutting-edge technologies, Data Science, and Decision Science, along with our proprietary "Aptus Accelerators," we enable organizations to identify risks and capitalize on key business opportunities. Our team of experts brings deep domain knowledge and technical expertise to extract valuable insights from complex datasets and drive impactful business outcomes. Job Title: Enterprise Data Architect (AWS) Experience : 15+ years Location : Bangalore Employment Type: Full-time Notice - Prefer with shorter notice or can join within 30 days About the Role: We are seeking a seasoned Enterprise Data Architect with over 12+ years of experience in designing, implementing, and optimizing enterprise data platforms. The ideal candidate will have deep expertise in cloud-native data architecture (AWS) and data engineering frameworks (Databricks, Spark) to drive large-scale digital transformation and AI/analytics initiatives. Key Responsibilities: Lead the enterprise data architecture strategy, ensuring scalability, performance, and alignment with business goals. Architect and implement data lakehouse solutions using Databricks on AWS for unified data management and analytics. Design end-to-end data pipelines, integration frameworks, and governance models across structured and unstructured data sources. Define data models, metadata management, and data quality frameworks for enterprise-wide adoption. Collaborate with data engineering, AI/ML, analytics, and business teams to enable real-time and batch data processing. Evaluate and integrate emerging technologies in data mesh, GenAI data pipelines, and automation frameworks. Provide technical leadership and mentorship to data engineering and architecture teams. Establish best practices for data security, lineage, compliance (GDPR, HIPAA), and cloud cost optimization. Partner with business stakeholders to define data modernization roadmaps and cloud migration strategies. Required Skills and Experience: 10-15 years IT experience with 5-8 years enterprise data architect Strong experience in Data Architecture, Data Engineering, or related domains. Proven experience architecting enterprise-scale data platforms using AWS (S3, Glue, Lambda, Redshift, EMR, Athena, Lake Formation, etc.). Hands-on expertise in Databricks (Delta Lake, Spark, Unity Catalog, MLflow). Strong experience with data modeling (dimensional, canonical, semantic models) and ETL/ELT pipelines. Deep understanding of data governance, master data management (MDM), and data cataloging tools. Proficient in SQL, Python, PySpark, and API-based data integration. Experience with modern data stack (Snowflake, dbt, Airflow, Kafka, etc.) is a plus. Strong understanding of AI/ML data readiness, metadata design, and data observability frameworks. Excellent communication and leadership skills to collaborate with technical and business teams. Certifications in AWS (Data Analytics / Solutions Architect) or Databricks preferred. Experienced in global onsite client handling role and managing senior management stakeholder interactions Preferred Qualifications: Experience in enterprise data strategy, governance frameworks, and migration of legacy systems to cloud. Exposure to GenAI data pipelines or LLM-based data preparation workflows. Strong background in data security, IAM, and compliance standards. Education: Bachelor’s or master’s degree in computer science, Information Systems, Data Engineering, or related field.