Data Architect

A result- oriented thought-leader to drive the development of the data engineering practice

A trusted advisor and business partner to customers across verticals, and consulting team leader who establishes engineering processes and skill development.

Technology skills (any of below):

• Data engineering: analytical data platforms, streaming, big data, EDW, data lakes, data governance, data mesh, Spark, Kafka, Snowflake, (2 from below: AWS, GCP, Azure) Transactional databases: Redis, Cassandra, MongoDB, (2 from below: AWS, GCP, Azure) ML and MLOps: VertexAI, Sagemaker, Dataiku, Databricks, mlflow

Essential functions

Responsibilities:

Trusted Advisor:

Pre-Sales and Consulting:

Technology Strategy and R&D:

assets and solutions strategy across multiple industries.

Engineering:

Business Development & Partnership:

Manage relationships with key technology partners(AWS, GCP, Azure) and industry analysts.

Requirements:

• Extensive practical experience in Big Data engineering, data governance, and cloud data
• platforms.
• Strong understanding of cloud-based architectures for data collection, data aggregation, reporting, and BI.
• Strong understanding of ML platforms and tooling including open-source, cloud native, and proprietary.
• Deep domain knowledge in at least one of the following industries: Retail, Finance, Manufacturing, Healthcare, Life Sciences.
• Experience in managing and delivering sophisticated analytical and data engineering programs at the enterprise scale.
• Managed key client relations worldwide and advised global technology and business leaders on innovation and data strategy.
• Experience with Big 4 consulting is a plus.

Qualifications

Experience with enterprise Architecture.

Would be a plus

Enterprise Architecture