Databricks Solution Architect Job Description

The successful candidate will be responsible for leading the practice's ambitious growth initiative with our most strategic cloud partners. This opportunity is scoped for high performing, high potential subject matter experts who are self-directed, entrepreneurial, highly collaborative, organized, diligent, and thoughtful. This role requires a domain expertise combined with the ability to task-organize, focus on the details, and sustain and drive progress over time.

For the right candidate, this role offers an opportunity to contribute to rapid revenue growth in one of the most exciting and dynamic segments of the market. This is an ideal opportunity for technologists seeking cross vertical and/or cross industry expertise. Among other career-enhancing considerations, this role provides opportunities to directly and indirectly manage teams.

The entire AIA leadership team is personally committed to the success of the architects on-boarded through this focused cloud hiring initiative.

Principal Responsibilities

Lead joint solution architecture discussions with customer architects/stakeholders and support development
Provide leadership for the transformation of customer requirements into visions, strategies, and roadmaps to implement data platforms, multi-cloud , cloud data warehouse with primary focus on Databricks
Independently lead client design workshops and provide tradeoffs and recommendations
Contribute to the Cognizant Data community by developing assets, thought leadership, etc.
Craft and manage solution/technical architecture for large scale data modernization and cloud data migration initiatives
Drive turnkey proposals for data platforms, analytics, built cost summaries, value propositions as part of cloud modernization, data portfolio rationalization

Technical Qualifications

Preferred cloud competencies:
Deeper Solution Architect skills in Databricks with deeper exposure to one of the clouds – AWS, Azure, GCP
Aware of PaaS services relating to Data, Analytics and end-point API interfaces - EMR/Dataproc/Snowflake etc.
Able to compare and contrast between best of technologies by layer – e.g, stream processing, messaging, search, etc.
High-level awareness of other partner technologies, which are alternative to native services like Snowflake, Cloudera, Talend, Informatica, Confluent, etc.
Exposure to native cloud data engineering technologies like AWS Glue, ADF, GCP datafusion, Bigquery etc

Key competencies

Excellent consulting, communication, influencing and facilitation skills, in particular problem solving/troubleshooting activities.
Lead key data architecture decisions, design of architectural roadmaps, database, data access and data technology architectures
Provide expertise on the overall data eco-system's engineering best practices, standards, architectural approaches, and complex technical resolutions
Holistic knowledge of solution architecture, including:

× Data layers and purpose

× Serverless compute

× Processing run time – ETL vs Spark run time, etc.

× Security controls around authentication, authorizations, encryption and certificates

× Recommend the migration tools and design data migration strategy

× Metadata and data catalogs

Excellent communication skills, preparing presentations, executive readouts

Key Experience

Successfully built and defended solution architecture with different levels of technical stakeholders – Business heads, enterprise architects, tech leads, etc.