Azure Data Architect

Azure Data Engineer - Key Role in Large-Scale Data Pipelines

• \
• Design and implement large-scale data pipelines and architectures.\
• Maintain high-quality data processing and analysis.\
• Collaborate with the team to achieve business transformation goals.\
• Ensure deep engineering expertise and innovative solutions are applied in all projects.\
• Implement and maintain large-scale data architectures using cutting-edge technologies such as Azure Data Factory, Databricks, SQL DB, Synapse, Stream Analytics, Glue, Airflow, Kinesis, Redshift, SonarQube, and PyTest.\
• Develop and maintain high-quality data models, integrate data from various sources, and manipulate and process large datasets efficiently.\
• Work closely with the development team to ensure seamless integration of data pipelines and architectures.\
• Participate in code reviews and contribute to the improvement of existing codebases.\
• Stay up-to-date with the latest industry trends, best practices, and emerging technologies in data engineering.\
• Engage in knowledge-sharing activities to enhance team capabilities and drive innovation.\
• Contribute to the development of technical documentation and share expertise with colleagues through blog posts, presentations, or training sessions.\
• Actively participate in brainstorming sessions to propose innovative solutions and enhancements.\
• Develop and maintain strong relationships with cross-functional teams, including sales, marketing, and customer success.\
• Assist in identifying areas for process improvements and collaborate with the team to implement changes.\
• Play an active role in onboarding new team members, providing guidance and support as needed.\
• Stay organized, prioritize tasks effectively, and meet deadlines while maintaining high-quality results.\
• Communicate complex technical concepts clearly and concisely to both technical and non-technical stakeholders.\
• Identify opportunities for growth and suggest strategic initiatives that align with business objectives.\
• Drive change management efforts to adopt new tools, processes, and methodologies.\
• Lead by example, demonstrate a growth mindset, and foster a culture of continuous learning and improvement.\
• Document and track progress against key performance indicators (KPIs) and establish meaningful metrics for success.\
• Offer feedback and suggestions to improve internal processes and optimize workflows.\
• Enhance overall efficiency, productivity, and quality through collaboration and idea sharing.\
• Support the organization's commitment to diversity, equity, and inclusion by promoting a culture of respect and empathy.\
• Ensure compliance with company policies, procedures, and standards.\
• Continuously develop skills and knowledge in data engineering and related areas.\
• Share domain expertise with other teams and departments to drive alignment and collaboration.\
• Build strong relationships with peers, managers, and external partners to leverage their expertise and resources.\
• Propose, plan, and execute events, workshops, and training programs to educate team members and enhance skills.\
• Encourage open communication and facilitate discussion among team members to promote teamwork and collaboration.\
• Collaborate with the leadership team to develop and implement strategies that drive business growth and success.\
• Advocate for the use of technology and digital solutions to drive business outcomes and improve customer experience.\
• Regularly review and update technical knowledge to stay current with industry developments.\
• Partner with the learning and development team to create customized training programs and materials.\
• Provide input on talent acquisition and retention strategies to attract top talent.\
• Contribute to the development of project proposals, pitches, and meeting materials.\
• Represent the team in meetings with stakeholders, senior leaders, and customers.\
• Provide insights and recommendations to improve internal processes and operations.\
• Drive cultural awareness and adoption of our values across the organization.\
• Conduct research on emerging trends, technologies, and innovations in the field of data engineering.\
• Create, curate, and manage content for the company blog, social media, or other channels.\
• Host webinars, workshops, or online sessions to share expertise and build thought leadership.\
• Assist in managing projects, coordinating activities, and setting priorities.\
• Recruit and lead ad-hoc teams to deliver critical projects or initiatives.\
• Establish and maintain effective working relationships with key stakeholders, including vendors, clients, and partners.\
• Oversee and manage budgets, financial plans, and other resource allocations.\
• Lead employee engagement activities and promotions.\
• Manage and prioritize competing tasks and responsibilities while meeting deadlines.\
• Develop and implement strategies to increase staff morale and job satisfaction.\
• Identify potential risks and develop contingency plans to mitigate them.\
• Recommend and implement new processes or systems to enhance operational efficiency and productivity.\
• Supervise and evaluate the work of team members, providing coaching and mentoring where necessary.\
• Make strategic recommendations to improve organizational effectiveness.\
• Stay informed about industry trends, competitor activity, and market conditions to inform decision-making.\
• Advance professional development through attending conferences, workshops, and courses.\
• Other duties as assigned.\