Data Architect

Role Description

As a Solutions Architect - Data Analytics, you will be responsible for designing and implementing robust data solutions that drive strategic decision-making. You will work closely with business stakeholders to understand their data needs, and then translate those needs into technical solutions. Your role will involve architecting and designing complex data pipelines, data warehouses, and data marts. Additionally, you will oversee the development and deployment of advanced analytics solutions.

Key Responsibilities:

• Collaborate with business stakeholders to understand their data needs and translate them into technical solutions.
• Define and enforce data architecture standards, guidelines, and best practices.
• Design and implement enterprise data models, including dimensional and normalized models.
• Develop data governance policies and procedures to ensure data quality and security.
• Design and implement hybrid and multi-cloud data strategies, seamlessly integrating data across various cloud platforms (AWS, Azure, GCP) to optimize performance and cost-efficiency.
• Collaborate with data engineers to design and optimize data pipelines and ETL processes.
• Design and implement enterprise data warehouses and data marts to support business intelligence and analytics.
• Optimize database performance through indexing, partitioning, and query optimization techniques.
• Ensure data quality through data profiling, cleansing, and validation.
• Implement data security measures to protect sensitive data.
• Collaborate with data scientists to design and deploy advanced analytics solutions.
• Implement data visualization and reporting tools to enable data-driven decision making.
• Utilize cloud-based data analytics tools and services (e.g., Databricks, Snowflake) to scale data processing and analysis.
• Lead and mentor a team of data engineers and data analysts.
• Work closely with IT teams to ensure alignment with overall IT strategy.

Requirements:

• Bachelor’s degree in computer science, Engineering, Information Systems, or a related field. Master’s degree is preferred.
• 7+ years of experience in data warehousing, data engineering, or data analytics roles.
• 3+ years of experience in (Conceptual, Logical, Physical) Dimensional Data Modeling.
• Hands-on experience in cloud-native technologies and platforms (AWS, Azure, GCP) will be an advantage.
• Certifications in data architecture, data engineering, or cloud platforms are highly valued.
• Experience using multiple SDLC methodologies and best practices, preferably in the development of Data Warehouse solutions.
• Strong proficiency in SQL, Python, and other data programming languages.
• Expertise in data integration, ETL processes, and data pipelines.
• Expertise in data modeling techniques (dimensional and normalized).
• Knowledge of cloud-based data warehousing and data lake solutions.
• Strong understanding of data visualization principles and methodologies with the ability to translate complex data into compelling visualizations.
• Strong understanding of metadata, data governess and data quality concepts.
• Experience in leading and mentoring teams.
• Ability to work independently and collaboratively.
• Strong analytical and problem-solving skills.
• Leadership and team management abilities.
• Excellent communication and presentation skills.