Data Architect

Job Description: Role & responsibilities* Design and lead enterprise data architectures that are scalable, secure, reliable, and aligned with business objectives.* Define data architecture strategies, standards, principles, and technology roadmaps.* Translate business requirements into data models, data platforms, integration architectures, and technical solutions.* Design and implement data warehouses, data lakes, lakehouses, and modern cloud-based data platforms.* Develop logical, physical, conceptual, and dimensional data models.* Design batch and real-time data pipelines using ETL/ELT and streaming technologies.* Architect data integration solutions across databases, applications, APIs, cloud platforms, and third-party systems.* Establish data governance, data quality, metadata management, data lineage, and master data management practices.* Design secure data architectures incorporating access controls, encryption, privacy, compliance, and data-protection standards.* Optimize data platforms for performance, scalability, availability, reliability, and cost efficiency.* Lead data migration, modernization, and cloud transformation initiatives.* Evaluate and recommend data technologies, tools, platforms, and architectural patterns.* Collaborate with data engineers, software engineers, BI teams, data scientists, cloud teams, security, and business stakeholders.* Conduct architecture reviews, data-model reviews, technology assessments, and performance evaluations.* Establish standards for data integration, storage, processing, retention, and lifecycle management.* Ensure data platforms support analytics, reporting, machine learning, and real-time business requirements.* Maintain data architecture documentation, data models, lineage diagrams, technical specifications, and standards.* Mentor data engineers and architects and provide technical leadership across data initiatives.Preferred candidate profile* 5 to 10 years of experience in data engineering, database development, data architecture, BI, or enterprise data management.* Proven experience designing and implementing enterprise-scale data architectures and platforms.* Strong expertise in data modeling, dimensional modeling, data warehousing, data lakes, and lakehouse architectures.* Advanced SQL skills and strong experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.* Experience with NoSQL databases such as MongoDB, Cassandra, DynamoDB, or similar technologies.* Hands-on experience with cloud data platforms such as AWS, Azure, or GCP.* Experience with modern data platforms and technologies such as Snowflake, Databricks, BigQuery, Redshift, or Azure Synapse.* Strong knowledge of ETL/ELT, data integration, batch processing, and real-time/streaming architectures.* Experience with Apache Spark, Kafka, Airflow, dbt, or similar data engineering technologies.* Strong understanding of data governance, data quality, metadata, data lineage, master data management, and data security.* Experience designing secure and compliant data architectures with appropriate access controls, encryption, and privacy mechanisms.* Knowledge of BI and analytics platforms such as Power BI, Tableau, or equivalent tools.* Experience leading data migration, modernization, cloud adoption, and large-scale data transformation projects.* Strong understanding of distributed systems, scalability, performance optimization, and cloud cost management.* Strong analytical, problem-solving, communication, documentation, and stakeholder-management skills.* Ability to provide technical leadership and mentor data engineers and development teams.* Bachelor's degree in Computer Science, Information Technology, Data Science, Computer Engineering, Statistics, Mathematics, or a related field; Master's degree is an advantage.