Data & Analytics Solutions Architect

Tata Consultancy Services (TCS) is an equal opportunity employer, and embraces diversity in race, nationality, ethnicity, gender, age, physical ability, neurodiversity, and sexual orientation, to create a workforce that reflects the societies we operate in. Our continued commitment to Culture and Diversity is reflected in our people stories across our workforce and implemented through equitable workplace policies and processes.

TCS has been serving the Canadian marketplace for more than 35 years and today is the technology partner of choice for many of the country's leading organizations. As one of the largest IT services providers in Canada and globally, TCS is aiming to become the world's largest AI-led technology services company and is enabling its clients to transform themselves across the full AI stack, from infrastructure to intelligence.

Rooted in the heritage and values of the Tata Group, TCS is focused on creating long-term value for its clients, investors, employees, and the communities it serves. With a highly skilled workforce supporting customers from coast to coast, TCS has consistently been recognized as a Top Employer by the Top Employers Institute, including a recent top ranking at the country level.

TCS also sponsors 14 of the world's most prestigious marathons and endurance events, including the TCS Toronto Waterfront Marathon, reflecting its commitment to health, sustainability, and community empowerment.

Skills Required

Must to Have

• Experience in Enterprise Data Architecture, Hadoop Ecosystem, Big Data Engineering, and Data Platform Modernization.
• Strong hands‑on expertise in Hadoop, HDFS, YARN, Hive, Spark, PySpark, Kafka, SQL, Python, Java, and Scala.
• Experience designing and implementing large‑scale Big Data and Data Lake architectures supporting analytics, reporting, and AI workloads.
• Strong understanding of Hadoop platform architecture, including HDFS, YARN, high availability, cluster management, workload optimization, and scalability.
• Experience in Enterprise Data Architecture, Hadoop Ecosystem, Big Data Engineering, and Data Platform Modernization.
• Strong hands‑on expertise in Hadoop, HDFS, YARN, Hive, Spark, PySpark, Kafka, SQL, Python, Java, and Scala.
• Experience designing and implementing large‑scale Big Data and Data Lake architectures supporting analytics, reporting, and AI workloads.
• Strong understanding of Hadoop platform architecture, including HDFS, YARN, high availability, cluster management, workload optimization, and scalability.
• Expertise in batch and distributed data processing using Spark, Hive, HBase, and MapReduce frameworks.
• Experience building data ingestion and streaming solutions using Kafka and Hadoop ecosystem tools.
• Strong knowledge of Data Engineering practices, including ETL/ELT, data integration, data quality, metadata management, lineage, observability, and DataOps.
• Experience with Data Lake, Data Warehousing, Enterprise Data Models, Master Data, and Data Governance frameworks.
• Strong understanding of security and governance controls, including Kerberos, Ranger, encryption, privacy, auditability, compliance, and controlled data access.
• Proven experience in architecture definition, HLD/LLD creation, migration planning, technical governance, production readiness, and performance optimization.
• Experience supporting platform modernization, cloud adoption, solutioning, effort estimation, and client‑facing technical discussions.
• Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements.

Preferred certifications in Hadoop, Spark, Cloud Data Engineering, Enterprise Architecture, Data Management, Security, or Big Data Platforms.

Roles and Responsibilities

• Engage with business and technology stakeholders to understand business objectives, data platform requirements, and modernization goals.
• Define end-to-end architecture for Hadoop and Big Data platforms supporting analytics, reporting, and AI workloads.
• Design scalable, secure, and high-performance Hadoop ecosystems using HDFS, YARN, Spark, Kafka, Hive, and related technologies.
• Architect data ingestion, batch processing, streaming, and data lake solutions for enterprise-scale environments.
• Define data models, data lake zones, governance frameworks, metadata management, lineage, and security standards.
• Lead Hadoop modernization, migration, and platform optimization initiatives to improve performance, scalability, and operational efficiency.
• Establish architecture standards, reusable frameworks, engineering best practices, and DataOps operating models.
• Provide technical leadership across solution design, implementation, testing, migration, deployment, and production support activities.
• Conduct architecture reviews, identify risks and dependencies, and guide teams on mitigation strategies and best practices.
• Drive performance tuning, capacity planning, reliability improvements, and infrastructure cost optimization.
• Collaborate with data engineers, platform teams, architects, vendors, and client stakeholders to deliver enterprise data solutions.
• Support solutioning, RFP responses, effort estimation, technical presentations, and client workshops.
• Mentor architects and engineers and contribute to hiring, capability development, and knowledge‑sharing initiatives.

Develop reusable accelerators, reference architectures, implementation frameworks, and technical best practices for Big Data platforms

TCS does not use artificial intelligence tools for candidate screening or evaluation. This post is for a current vacancy. The hiring process includes an initial screening, followed by a technical evaluation and managerial discussion.

Tata Consultancy Services Canada Inc. is committed to meeting the accessibility needs of all individuals in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code (OHRC). Should you require accommodation during the recruitment and selection process, please inform Human Resources.