Platform Engineer

📋 Description

• Develop and construct the organization's data infrastructure and architecture.

• Collaborate with business leaders and domain experts to convert strategic goals into data architecture capabilities.

• Offer insights regarding the evolving requirements for database/datalake storage and usage within the company, along with potential solutions.

• Set standards for data platforms, integration processes, analytics, and AI enablement.

• Evaluate database/datalake implementation strategies to ensure compliance with company policies and applicable external regulations.

• Support ongoing organizational decisions regarding data infrastructure and architecture, and shape the data strategy.

• Serve as a trusted advisor on how data architecture can drive revenue, enhance efficiency, and mitigate risk, while advising leadership on data investment strategies.

• Manage the transition of data from legacy systems to new solutions.

• Apply architectural principles, specific product guidelines, security protocols, and usability design standards as necessary.

• Influence decision-making among various stakeholders and assist engineering teams in addressing complex technical issues.

• Propel the growth of analytics and AI services by integrating scalable design patterns into all engagements.

• Provide thought leadership, reusable resources, and frameworks to enhance the Data & AI practice.

⛳️ Requirements

• Minimum of 3 years of experience in data platform architecture, analytics, or AI/ML.

• Proven experience in translating business needs into technical design documentation.

• Demonstrated experience in architecting and securing big data solutions.

• Proficiency with Azure.

• Competence in Python and SQL.

• Familiarity with data movement and ETL processes.

• Knowledge of data governance and metadata management tools.

• Strong communication abilities.

• Capability to work effectively with an international team.

• Preferred experience in building data lakes.

• Preferred experience in developing data products.

• Experience in team leadership and stakeholder engagement.

• Understanding of Databricks, Docker, Kubernetes, or Azure Functions.

• Strategic thinker with a strong focus on execution.

• Ability to collaborate within cross-functional teams.

• Keen attention to detail and commitment to data quality.

🏝️ Benefits

• Opportunities for professional growth and development.

• Competitive salary and performance-based incentives.

• Flexible working arrangements.

• Access to the latest tools and technologies in data and AI.

• Collaborative and innovative work environment.