Job Summary:We are seeking a seasoned and strategic Data Analytics Architect to lead the design and implementation of enterprise-wide analytics architecture. The successful candidate will architect data platforms, guide data governance, ensure scalability of data solutions, and serve as a bridge between business needs and data technology. This role requires strong technical expertise, leadership capabilities, and a vision for turning data into a strategic asset.
Key Responsibilities:Architect and design end-to-end data analytics platforms including data pipelines, data lakes, warehouses, and reporting environments. Define and enforce data architecture standards, frameworks, and best practices. Work closely with data engineers, analysts, and business stakeholders to ensure data solutions align with business needs. Implement and optimize data integration and ETL/ELT processes across multiple systems. Guide and support the adoption of cloud-based data platforms (e.g., Azure, AWS, Google Cloud). Evaluate and select appropriate tools and technologies for data storage, processing, modeling, and visualization. Ensure data quality, security, and compliance with regulatory and corporate policies. Develop data governance models and metadata management frameworks. Provide technical leadership on analytics projects and mentor junior team members. Collaborate with enterprise architects and IT leadership to align data architecture with broader enterprise architecture.
Requirements:Education & Experience:Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field. Minimum 8+ years of experience in data architecture, business intelligence, or data engineering. Proven experience in designing and delivering enterprise-scale analytics platforms. Technical Skills:Expertise in data modeling (dimensional and normalized) and database technologies (SQL Server, Oracle, Postgre SQL, etc.). Strong hands-on experience with Big Data and cloud platforms (e.g., Azure Synapse, AWS Redshift, Snowflake, Google Big Query). Deep understanding of ETL tools and frameworks (e.g., Informatica, Talend, Azure Data Factory). Proficiency in BI tools such as Power BI, Tableau, or Looker. Knowledge of data governance, master data management (MDM), and metadata management. Familiarity with data science workflows and tools (e.g., Python, R, Databricks, Spark). Soft Skills:Strong communication skills to interact with technical and non-technical stakeholders. Leadership, strategic thinking, and problem-solving capabilities. Ability to drive innovation and continuous improvement in data solutions. Preferred Qualifications:Certifications in Azure, AWS, GCP, or relevant data technologies. Experience with AI/ML integration into data pipelines. Experience working in Agile and Dev Ops environments.