Solutions Architect

As a Solution Architect specializing in Data Analytics, you will play a critical role in designing and implementing scalable data solutions that empower strategic business decisions. You will engage closely with business stakeholders to gather and understand their data requirements, translating these into effective technical architectures. Your expertise will be essential in building complex data pipelines, data warehouses, and data marts, while also overseeing the deployment of advanced analytics capabilities to drive insights across the organization.

Key Responsibilities:
- Collaborate with business stakeholders to capture data needs and convert them into technical solutions.
- Define and enforce data architecture standards, guidelines, and best practices across projects.
- Design and implement enterprise data models, including both dimensional and normalized schemas.
- Develop and maintain data governance policies to ensure data quality, security, and compliance.
- Architect hybrid and multi-cloud data strategies, integrating data seamlessly across platforms such as AWS, Azure, and GCP to enhance performance and cost-efficiency.
- Work alongside data engineers to design, optimize, and maintain data pipelines and ETL workflows.
- Lead the design and implementation of enterprise data warehouses and data marts to support business intelligence and analytics initiatives.
- Optimize database performance through techniques like indexing, partitioning, and query tuning.
- Ensure data integrity by performing data profiling, cleansing, and validation activities.
- Implement robust data security measures to safeguard sensitive information.
- Collaborate with data scientists to design and deploy advanced analytics and machine learning solutions.
- Utilize cloud-based analytics tools such as Databricks and Snowflake to scale data processing and analysis.
- Lead, mentor, and develop a team of data engineers and analysts, fostering a collaborative and high-performance environment.
- Partner with IT teams to ensure data architecture aligns with the overall IT strategy and infrastructure.

Required Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline; Master’s degree preferred.
- Minimum of 7 years’ experience in data warehousing, data engineering, or analytics roles.
- At least 3 years of hands-on experience in dimensional data modeling (conceptual, logical, and physical).
- Proficiency in cloud-native platforms such as AWS, Azure, or GCP is highly advantageous.
- Strong expertise in SQL, Python, and other relevant data programming languages.
- Extensive experience in data integration, ETL processes, and building scalable data pipelines.
- Deep knowledge of data modeling techniques, including both dimensional and normalized approaches.
- Familiarity with cloud-based data warehousing and data lake architectures.
- Solid understanding of data visualization principles and the ability to translate complex datasets into clear, actionable insights.
- Comprehensive knowledge of metadata management, data governance, and data quality frameworks.
- Proven leadership experience, including mentoring and managing technical teams.
- Excellent analytical, problem-solving, communication, and presentation skills.
- Ability to work effectively both independently and collaboratively within cross-functional teams.

Preferred Qualifications and Benefits:
- Certifications in data architecture, data engineering, or cloud platforms are highly valued.
- Experience with multiple software development lifecycle (SDLC) methodologies, particularly in data warehouse solution development.
- Exposure to advanced cloud-based analytics tools such as Databricks and Snowflake enhances candidate suitability.

This role offers the opportunity to lead innovative data initiatives within a dynamic environment, driving impactful business outcomes through strategic data architecture and analytics excellence.