Principal Data Engineer

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Job Overview

Key Responsibilities

• Technical and Business Solutions Development: Lead & develop technical and business solutions for Data & Analytics Products
• Project Leadership: Lead multiple projects simultaneously, creating solutions, frameworks, and POCs to address emerging business solutions and leverage emerging technologies in data analytics.
• Architecture Vision: Present Data & Analytics architecture vision and solutions to stakeholders.
• Trusted Advisor: Position yourself as a Trusted Advisor to stakeholders by focusing on achieving their desired business outcomes.
• Innovation Partnership: Partner with the innovation team to drive repeatable frameworks, accelerators, and business point solutions for Financial services, Insurance, Healthcare, Retail or Travel Hospitality industry verticals.
• Value Demonstration: Demonstrate and communicate the value of Data & Platform throughout engagements, from demos to Proof of Concepts to workshops and design sessions.
• Hands-on Expertise: Maintain excellent hands-on abilities to design, build, and engineer solutions as needed, ensuring high performance and availability of data systems.
• Collaboration: Collaborate deeply with peer teams such as product marketing, sales etc. for activities such as creating product marketing material, website content, go to market plans for developed products/solutions.
  

Required Skills And Experience

• Minimum of 10 years of experience in Data Analytics, AI related fields.
• Strong experience architecting and designing end-to-end Data analytics solutions. Experience as a Data Solutions architect / Full stack Data Engineer or similar with either of cloud / analytics platform is required.
• Experience working in on-prem, Cloud (any of Azure, AWS, GCP)
• Strong understanding of data warehousing concepts, ML Engineering, AI Integration and best practices is required.
• Skilled in designing scalable and efficient data architectures
• Extensive Experience with either of the cloud data analytics platforms (Snowflake, Databricks, AWS, Azure): Proven track record of implementing and managing Data Cloud solutions, including setting up environments, configuring databases, and optimizing performance.
• Knowledge of machine learning and AI integration with data platforms.
• Experience working in SQL and Python for data manipulation and automation.
• Experience with Data Engineering, ETL/ELT tools, Data Visualization and processes. Experience working in any of the Data engineering tools
• Familiarity with any of the Data visualization tools.
• Excellent problem-solving skills and the ability to troubleshoot complex data issues.
• Strong communication skills, with the ability to convey technical concepts to non-technical stakeholders.
• Proven experience in leading small teams and managing projects from inception to delivery.
  

Prefered Skills

• Hands-on experience with other cloud data platforms, such as Databricks, AWS Redshift, Google BigQuery, or Azure Synapse.
• Experience with migration / modernization from on-prem to Cloud from conception to delivery is preferred.
• Familiarity with data governance and security best practices.
• Experience with BI and data visualization tools such as Power BI, Tableau, or Looker.