Data Architectural Specialist

Job Title: Data Architectural Specialist

Overview:

The ideal candidate for this role will have a proven track record of designing and implementing large-scale data systems and architectures.

Key Responsibilities:

• \
• Design and develop scalable data pipelines using distributed data processing technologies.\
• Develop and maintain production-ready ETL (Extract, Transform, Load) pipelines using Python and SQL.\
• Collaborate with cross-functional teams to design and implement data solutions that meet business requirements.\
• Implement data lake and data lake house patterns to store and process large datasets.\
• Optimize ETL performance and reduce costs by implementing efficient data processing techniques.\
• Stay up-to-date with industry trends and emerging technologies in data engineering.\
• Design and develop high-performance data storage solutions.\
• Develop and maintain data quality control processes.\
• Collaborate with the data science team to integrate data into machine learning models.\
• Document and maintain data architecture designs.\
• Assist in planning and implementing new data-related projects.\
• Develop and maintain technical documentation.\
• Assist in capacity planning and resource allocation for data infrastructure.\
• Develop and maintain disaster recovery and backup procedures.\
• Implement data governance policies and procedures.\
• Collaborate with the security team to ensure data security and compliance.\
• Develop and maintain data visualizations and reports.\
• Provide data insights and recommendations to stakeholders.\
• Collaborate with the business intelligence team to develop and maintain dashboards and reports.\
• Develop and maintain data warehousing and ETL solutions.\
• Collaborate with the data integration team to integrate data from various sources.\
• Develop and maintain data catalogs and metadata management systems.\
• Collaborate with the data governance team to ensure data quality and integrity.\
• Develop and maintain data lineage and impact analysis.\
• Collaborate with the data analytics team to develop and maintain advanced analytics models.\
• Develop and maintain data storytelling and communication strategies.\
• Collaborate with the data visualization team to develop and maintain interactive visualizations.\
• Develop and maintain data-driven business cases.\
• Collaborate with the business development team to develop and maintain strategic partnerships.\
• Develop and maintain data monetization strategies.\
• Collaborate with the marketing team to develop and maintain data-driven marketing campaigns.\
• Develop and maintain data privacy and security protocols.\
• Collaborate with the legal team to ensure data compliance with regulatory requirements.\
• Develop and maintain data risk management strategies.\
• Collaborate with the IT team to develop and maintain data infrastructure.\
• Develop and maintain data standards and best practices.\
• Collaborate with the quality assurance team to ensure data quality and integrity.\
• Develop and maintain data testing and validation procedures.\
• Collaborate with the deployment team to deploy data solutions.\
• Develop and maintain data deployment scripts.\
• Collaborate with the operations team to monitor and maintain data infrastructure.\
• Develop and maintain data monitoring and logging procedures.\
• Collaborate with the support team to troubleshoot and resolve data-related issues.\
• Develop and maintain data troubleshooting guides.\\/ul>\

Requirements:

Proficient in Python, including popular packages like Pandas and NumPy.

Strong background in distributed data processing and storage technologies.

Experience with at least one cloud platform, such as Azure, AWS, or GCP.

Knowledge of data structures, algorithms, and software engineering practices.

Experience with code version control tools like Git.

Strong analytical and problem-solving skills.

Ability to work in a fast-paced environment and adapt to changing priorities.

Excellent communication and collaboration skills.

Proven track record of delivering high-quality results.

Ability to think strategically and make informed decisions.

Experience with data governance and compliance regulations.

Knowledge of data security and privacy best practices.

Ability to work effectively in a team environment.

Strong attention to detail and ability to prioritize tasks.

Ability to communicate complex technical concepts to non-technical stakeholders.

Experience with data storytelling and communication strategies.

Knowledge of data visualization tools and technologies.

Ability to develop and maintain data visualizations and reports.

Experience with data-driven business cases and strategic partnerships.

Knowledge of data monetization strategies and data-driven marketing campaigns.

Ability to develop and maintain data privacy and security protocols.

Experience with data risk management strategies and compliance with regulatory requirements.

Knowledge of data standards and best practices.

Ability to develop and maintain data testing and validation procedures.

Experience with data deployment scripts and deployment procedures.

Knowledge of data monitoring and logging procedures.

Ability to develop and maintain data troubleshooting guides.

Benefits:

Opportunity to work on cutting-edge data engineering projects.

Collaborative and dynamic work environment.

Professional growth and development opportunities.

Competitive salary and benefits package.

Flexible working hours and remote work options.

Access to cutting-edge technology and tools.

Opportunity to work with a talented team of data engineers and scientists.

Recognition and rewards for outstanding performance.

Opportunity to contribute to the company's success and growth.

Others:

Must be willing to learn and adapt to new technologies and tools.

Must be able to work effectively in a team environment.

Must be able to communicate complex technical concepts to non-technical stakeholders.

Must be able to develop and maintain data visualizations and reports.

Must be able to work effectively in a fast-paced environment and adapt to changing priorities.

Must be able to think strategically and make informed decisions.

Must be able to communicate effectively with cross-functional teams.

Must be able to develop and maintain data storytelling and communication strategies.

Must be able to work effectively in a collaborative and dynamic work environment.

Must be able to recognize and respond to opportunities for professional growth and development.

Nice to Have:

Experience with Azure Databricks.

Knowledge of DevOps principles and ETL pipeline orchestration.

Certifications in Databricks, Azure, AWS, or GCP.