Data Architect

As a Data Architect, you will be responsible for designing and governing scalable big data and analytics platforms on leading cloud platforms such as AWS, Azure, or GCP. Your role will involve working closely with sales and delivery teams to shape solutions for prospective and existing clients. You will combine hands-on architecture, technical leadership, and pre-sales responsibilities with a strong focus on SQL, Python, and modern data engineering practices. Key Responsibilities: - Design and own end-to-end data architectures, including data lakes, data warehouses, and streaming pipelines using big data technologies like Spark, Kafka, and Hive on public cloud platforms. - Define canonical data models, integration patterns, and governance standards to ensure data quality, security, and compliance across the organization. - Lead pre-sales activities by assessing client requirements, running discovery workshops, defining solution blueprints, sizing and estimating effort, and contributing to RFP/RFI responses and proposals. - Build and review PoCs/accelerators using SQL and Python (e.g., PySpark, notebooks) to demonstrate feasibility, performance, and business value to customers. - Collaborate with data engineers, BI/ML teams, and application architects to ensure the designed architecture is implemented as intended and is cost-efficient, scalable, and reliable. - Establish best practices for data security, access control, and lifecycle management in alignment with regulatory and enterprise policies. - Monitor and continuously optimize data platforms for performance, reliability, and cost, leveraging cloud-native services and observability tools. - Provide architectural guidance and mentoring to engineering teams; review designs and code for critical data components. Required Skills & Experience: - 12-16 years of overall experience in data engineering/analytics, with 4+ years as a Data/Big Data Architect. - Strong expertise in SQL (analytical queries, performance tuning) and Python for data processing and automation. - Hands-on experience with big data frameworks and tools such as Spark, Kafka, Hadoop ecosystem, distributed file systems, and modern ETL/ELT pipelines. - Practical experience on at least one major cloud platform (AWS, Azure, or GCP) with services such as data lakes, warehouse services (Redshift, Snowflake, BigQuery, Synapse), and orchestration tools. - Proven pre-sales exposure: client workshops, solution design, RFP/RFI responses, effort estimation, and building PoCs or demos. As a Data Architect, you will be responsible for designing and governing scalable big data and analytics platforms on leading cloud platforms such as AWS, Azure, or GCP. Your role will involve working closely with sales and delivery teams to shape solutions for prospective and existing clients. You will combine hands-on architecture, technical leadership, and pre-sales responsibilities with a strong focus on SQL, Python, and modern data engineering practices. Key Responsibilities: - Design and own end-to-end data architectures, including data lakes, data warehouses, and streaming pipelines using big data technologies like Spark, Kafka, and Hive on public cloud platforms. - Define canonical data models, integration patterns, and governance standards to ensure data quality, security, and compliance across the organization. - Lead pre-sales activities by assessing client requirements, running discovery workshops, defining solution blueprints, sizing and estimating effort, and contributing to RFP/RFI responses and proposals. - Build and review PoCs/accelerators using SQL and Python (e.g., PySpark, notebooks) to demonstrate feasibility, performance, and business value to customers. - Collaborate with data engineers, BI/ML teams, and application architects to ensure the designed architecture is implemented as intended and is cost-efficient, scalable, and reliable. - Establish best practices for data security, access control, and lifecycle management in alignment with regulatory and enterprise policies. - Monitor and continuously optimize data platforms for performance, reliability, and cost, leveraging cloud-native services and observability tools. - Provide architectural guidance and mentoring to engineering teams; review designs and code for critical data components. Required Skills & Experience: - 12-16 years of overall experience in data engineering/analytics, with 4+ years as a Data/Big Data Architect. - Strong expertise in SQL (analytical queries, performance tuning) and Python for data processing and automation. - Hands-on experience with big data frameworks and tools such as Spark, Kafka, Hadoop ecosystem, distributed file systems, and modern ETL/ELT pipelines. - Practical experience on at least one major cloud platform (AWS, Azure, or GCP) with services such as data lakes, warehouse services (Redshift, Snowflake, BigQuery, Synapse), and orchestration tools. - Proven pre-sales exposure: client workshops, solution desi