Solution Architect

Job Description Roles & Responsibilities Engineering Services are seeking a Solution Architect with hands-on expertise in data engineering and solution architecture. This position bridges the gap between high-level business requirements and technical execution, defining the architecture of scalable data pipelines, robust storage solutions, and high-performance analytics environments. The responsibilities include prototyping complex integrations and ensuring that data infrastructure is robust, secure, resilient, and optimized for scale-up. As a practitioner in this role, the Solution Architect will be responsible for translating business needs into technical solutions, leveraging your expertise to drive the design and implementation of data-driven systems. Key Responsibilities Architectural Design: Lead the design of end-to-end solution and data architectures, including ingestion, processing, storage, and visualization layers. Infrastructure Strategy: Define cloud-native or hybrid infrastructure strategies that support high-volume data processing and real-time analytics. Hands-on Development: Develop Proof of Concepts (PoCs) and core framework components for data pipelines (e.g. ETL) to ensure architectural feasibility. Database Governance: Evaluate and select appropriate data stores (Relational, NoSQL, Graph, Vector) based on specific use-case requirements like latency, throughput, and consistency. Performance Optimization: Audit existing data systems to identify bottlenecks and implement strategies for cost-optimization and query performance tuning. Technical Leadership: Provide technical leadership in ensuring best practices in various areas including CI/CD and documentation. Solution Architecture: Develop and maintain a deep understanding of the corporate's technology landscape, including applications, data flows, and infrastructure, to identify opportunities for improvement and optimization. Legacy Modernization: Experience migrating on-premise infrastructure to cloud-native architectures. Containerization: Experience with Docker and Kubernetes for deploying data services. Cloud Infrastructure: Expert-level experience with at least one major cloud provider (AWS, Azure, or GCP) and their native data services. Data Processing: Strong proficiency in batch and stream processing. Programming: Advanced coding skills in Python, or Java, along with expert-level SQL. Database Systems: Extensive experience managing and querying various systems: Relational: PostgreSQL, MySQL, SQL Server, NoSQL/NewSQL: MongoDB, Cassandra, Warehousing/Lakehouses: Snowflake, Databricks, BigQuery. Enterprise Architecture: Knowledge of enterprise architecture principles, including business architecture, information architecture, and technology architecture. Desired Candidate Profile Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems, or a related field. Minimum of 15 years in IT, with at least 4 years in a Solution Architect or Lead Data Engineer role. Proven track record of delivering at least two large-scale enterprise data platform migrations or greenfield builds. Preferred qualifications and experience: The certifications are TOGAF, ITIL, or similar.AI/ML Integration experience architecting Feature Stores and MLOps pipelines to support machine learning workflows.Governance Tools familiarity with data cataloging and governance tools. Company Industry Oil & GasPetroleum Department / Functional Area IT Software Keywords Solution Architect Get real-time job updates only on our App