Senior Data Architect

11 hours ago


Yelahanka, India L&T Technology Services Full time

Primary Responsibilities: - Data Strategy & Governance: Define the end-to-end enterprise data architecture strategy (including data ingestion, storage, processing, and consumption) to support all Digital Products (AI, Analytics, IoT). - Blueprint & Modeling: Create and govern enterprise data models, data lake/mesh blueprints, and data governance frameworks (e.G., data quality, lineage, access control). - Platform Selection: Lead the selection, design, and optimization of Cloud-based data platforms (e.G., Snowflake, Databricks, specific Hyperscaler services) to maximize performance and cost-efficiency. - Security & Compliance: Ensure all data architectures meet strict industry-specific security, regulatory, and privacy requirements. Primary Skills: - Experience: 15-18+ years in data-focused roles, with 7+ years in a Lead/Principal Data Architect or Chief Data Architect role. - Cloud Data Expertise: Deep hands-on experience designing large-scale data platforms on at least one major Hyperscaler (AWS, Azure, or GCP). - Data Modeling Mastery: Expertise in various modeling techniques (3NF, Dimensional, Data Vault) and patterns (Data Lake, Data Warehouse, Data Mesh). - Big Data Technologies: Proficiency with distributed data processing technologies (e.G., Spark, Hadoop ecosystem, Kafka). * Leadership: Proven ability to influence executive decisions and lead technical teams in complex data migrations and modernization efforts. Secondary Skills: - Expertise in AI/ML Ops Data Pipelines and feature stores. - Certification in Cloud Data Engineering (e.G., Google Cloud Data Engineer, AWS Data Analytics Specialty). - Experience with Data Virtualization technologies. - Knowledge of modern data governance tools and practices (e.G., Collibra, Alation). - Prior experience with data related to Digital Twin implementation. Domain Skills- Deep domain expertise in at least one of the following: Automotive/ Industrial Products/ Plant Engineering Understanding of industry-specific digital use cases (e.G., connected vehicles, predictive maintenance, digital manufacturing).



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