Solutions Architect

As a Solution Architect - Data Analytics, you will play a pivotal role in designing and implementing comprehensive data solutions that empower strategic decision-making across the organization. You will collaborate closely with business stakeholders to understand their data requirements and translate these into scalable technical architectures. Your expertise will be essential in developing complex data pipelines, data warehouses, and data marts, while also overseeing the deployment of advanced analytics solutions to drive business insights.

Key Responsibilities:
- Collaborate with business stakeholders to gather and analyze data needs, converting them into effective technical solutions.
- Define and enforce data architecture standards, guidelines, and best practices to maintain consistency and quality.
- Design and implement enterprise data models, including both dimensional and normalized structures.
- Develop and maintain data governance policies to ensure data quality, security, and compliance.
- Architect hybrid and multi-cloud data strategies, integrating data across platforms such as AWS, Azure, and GCP to optimize performance and cost-efficiency.
- Work alongside data engineers to design, build, and optimize data pipelines and ETL processes.
- Lead the design and deployment of enterprise data warehouses and data marts supporting business intelligence and analytics initiatives.
- Enhance database performance through indexing, partitioning, and query optimization techniques.
- Ensure data integrity by conducting data profiling, cleansing, and validation activities.
- Implement robust data security measures to safeguard sensitive information.
- Partner 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 capabilities.
- Lead and mentor a team of data engineers and analysts, fostering professional growth and collaboration.
- Collaborate with IT teams to align data architecture strategies with overall IT objectives and infrastructure.

Required Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field; Master’s degree preferred.
- Minimum of 7 years’ experience in data warehousing, data engineering, or data analytics roles.
- At least 3 years of hands-on experience with dimensional data modeling (conceptual, logical, physical).
- Proficient in SQL, Python, and other relevant data programming languages.
- Strong expertise in data integration, ETL processes, and building data pipelines.
- Deep understanding of data modeling techniques, including dimensional and normalized models.
- Experience with cloud-native technologies and platforms such as AWS, Azure, and GCP.
- Knowledge of cloud-based data warehousing and data lake solutions.
- Familiarity with metadata management, data governance, and data quality concepts.
- Proven leadership skills with experience in mentoring and managing technical teams.
- Excellent analytical, problem-solving, communication, and presentation abilities.
- Ability to work independently and collaboratively within cross-functional teams.
- Experience applying multiple SDLC methodologies, particularly in data warehouse development.

Preferred Qualifications and Benefits:
- Certifications in data architecture, data engineering, or cloud platforms are highly valued.
- Experience with advanced data visualization tools and the ability to translate complex datasets into clear, actionable insights.
- Exposure to hybrid and multi-cloud environments to design cost-effective and scalable data solutions.

This role offers the opportunity to lead innovative data initiatives within a dynamic environment, working with cutting-edge cloud technologies and advanced analytics tools. You will be instrumental in shaping the organization’s data strategy while mentoring a talented team of professionals.