Data Platform Architect

About Mrikal: Mrikal is a leading product studio specializing in digital solutions across Pharma, Retail, Oil & Gas, and Edtech industries. Our multidisciplinary team excels in design, development, deployments, data engineering, and AI. We are committed to delivering world-class solutions through good architecture, data practices, embedded AI, user empathy, and growth hacks.

About the Role:
We are seeking an experienced Data Platform Architect to design and implement scalable, secure, and high-performance data solutions that drive business value. In this role, you will be responsible for architecting and overseeing the development of a modern data platform, ensuring it meets the evolving needs of our clients. You will solve complex analytical problems to bring data to insights and enable the use of ML and AI at scale for our clients. You will work closely with cross-functional teams, including data engineers, analysts, and business stakeholders, to translate business requirements into robust data architectures.

Responsibilities:
• Design and architect modern data platforms and solutions that support various data-centric products and services, leveraging cloud technologies, data lakes, data warehouses, and modern data processing frameworks.
• Organize and lead workshops and design sessions with stakeholders, including clients, team members, and cross-functional partners, to capture requirements, understand use cases, personas, key business processes, brainstorm solutions, and align on data architecture strategies and projects.
• Evaluate and recommend suitable technologies and tools for data ingestion, processing, storage, and analysis, such as Databricks, Snowflake, and other cloud-based data platforms.
• Develop and enforce data architecture standards, best practices, and governance policies to ensure data quality, security, and compliance with regulatory requirements.
• Collaborate with data engineers, developers, and analysts to design and implement efficient data pipelines, ETL/ELT processes, and data models that support business intelligence, machine learning, and advanced analytics use cases.
• Optimize data architectures for performance, scalability, and cost-effectiveness, leveraging cloud-native services and technologies.
• Provide technical leadership and mentorship to cross-functional teams, fostering a culture of innovation and continuous learning.
• Stay up-to-date with emerging data technologies, trends, and best practices, and champion their adoption within the organization.

Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in designing and implementing large-scale data platforms and solutions, with a strong focus on cloud technologies.
• Familiarity with fraud detection and prevention techniques, including rule-based and machine learning approaches for fraud analytics.
• Proven experience in designing and implementing data solutions for the telecom and finance industries, including regulatory reporting, risk management, and financial analytics.
• Experience in designing and implementing data architectures for telecom use cases, such as network data analysis, customer experience management, and fraud detection.
• Proven expertise in designing and optimizing data architectures for data lakes, data warehouses, and modern data processing frameworks like Apache Spark, Databricks, and Snowflake.
• Experience with big data technologies and frameworks for processing large volumes of structured and unstructured data from various sources (e.g., Apache Kafka, Apache NiFi, Apache Hadoop).
• Solid understanding of data modeling techniques, ETL/ELT processes, and data integration patterns.
• Experience with cloud platforms such as Google Cloud Platform, AWS, and Azure, and their data services and tools.
• Strong proficiency in SQL and at least one programming language (e.g., Python, Java, Scala).
• Knowledge of data governance, data security, and compliance frameworks (e.g., GDPR, HIPAA).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
• Familiarity with agile methodologies and project management practices.