Senior Data Architect

3 days ago

Melbourne, Victoria, Australia Cognizant Full time

About the Role:

Cognizant is seeking a highly skilled Senior Data Architect to join our growing Data & AI practice. As a transformative technical leader, you will drive innovation and excellence in data engineering and cloud solutions.

This senior role demands a visionary approach to solving complex business challenges through cutting-edge Databricks technologies. You will be responsible for elevating our practice's technical capabilities, establishing thought leadership, and creating breakthrough solutions for enterprise clients.

Key Responsibilities:

  1. Serve as the technical visionary and strategic leader for Databricks implementations across our consulting practice
  2. Collaborate closely with product teams at Databricks and cloud providers to drive innovation
  3. Develop and drive advanced data engineering strategies leveraging Databricks platform capabilities
  4. Lead complex, large-scale Databricks transformation initiatives for enterprise clients
  5. Understand customer objectives, goals and challenges to design innovative solutions
  6. Create and evangelize innovative architectural patterns and reusable solution frameworks
  7. Mentor and develop a high-performing team of data engineering professionals
  8. Provide thought leadership through technical publications, conference speaking, and industry engagement
  9. Design and implement advanced data solutions using Databricks, focusing on scalability, performance, and business value
  10. Act as the primary technical expert and escalation point for complex Databricks challenges
  11. Represent Cognizant in industry forums and meetups
  12. Mentoring junior engineers and foster knowledge sharing within the team

About You:

You need to be someone that can deal with ambiguity, thrive on change, and manage your own time effectively. We want someone that genuinely focuses on client outcomes, with a high degree of integrity. At Cognizant we value consultants that have a high IQ, enjoy problem solving, a willingness to serve. You will need to be confident presenting to both business and technology stakeholders, leading cross functional geographically dispersed teams, and have strong negotiating and collaboration for outcomes skills.

Requirements:

  1. 7-10 years of progressive experience in data engineering, with deep expertise in Databricks platform
  2. Advanced certifications in Databricks, Azure, and/or AWS data technologies
  3. Mastery of Databricks core components like DataFrames, Datasets, Spark SQL, Delta Lake, Databricks Notebook, DBFS, and Databricks Connect.
  4. Expert-level proficiency in Databricks core components (Delta Lake, Spark SQL, DataFrames)
  5. Advanced data architecture and platform design
  6. Machine learning pipelines and data engineering frameworks
  7. Strong track record of designing and implementing enterprise-scale data platforms
  8. Proven ability to translate complex technical concepts for business leadership
  9. Demonstrated success in developing innovative data solutions that drive measurable business outcomes
  10. Strong understanding of data architecture principles, including data modelling, ETL processes, data governance, data quality, privacy and security controls.
  11. Excellent communication skills: Strong written and verbal communication skills to effectively collaborate with team members and stakeholders.
  12. Familiarity with AWS or Azure for deploying and optimising Databricks environments.

Additional Skills:

  1. Expertise in machine learning pipelines, Spark Streaming, Databricks AutoML, Delta Live Tables, Databricks Unity Catalog, and Databricks Serverless Computing.
  2. Designing and implementing DataOps & Data Mesh aligned frameworks to optimise data platforms for cost, value, flexibility and efficiency.

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