Big Data Architect – IT Consultant Master

Job Summary:

We are seeking an experienced IT Consultant to design, develop, and maintain an enterprise Big Data/Data Lake architecture as part of the Data Modernization Effort. This role supports enterprise data operations including IoT/Smart City projects, the enterprise data warehouse, open data portal, and data science applications — working alongside DC's Chief Data Officer team on a Databricks/Azure-based platform.

Key Responsibilities:

·        Coordinate IT project management, engineering, maintenance, QA, and risk management

·        Plan, coordinate, and monitor project activities across the data platform lifecycle

·        Develop technical applications and support real-time database, network, and graphics/logic systems

·        Establish and enforce standards/procedures for system design, development, and documentation

·        Perform application upgrades, troubleshoot issues, and provide user training

·        Ensure project lifecycle compliance with District standards and procedures

·        Integrate platform with enterprise tools (Esri, Tableau, MicroStrategy, API Gateways, Oracle)

Required Skills & Certifications:

·        Bachelor's degree in IT or related field (or equivalent experience)

·        16 years: planning/coordinating/monitoring projects and ensuring standards compliance

·        5 years: Big Data platforms (Databricks, Data Lakes), Azure cloud architecture/security/storage, data operations (runtime, warehousing, pipelines, cost/user management), data visualization tools (Tableau, MicroStrategy, ArcGIS, Kibana, Oracle), SQL/NoSQL querying, data pipeline modeling/ingestion

·        3 years: REST/SOAP API & web services, real-time streaming/event processing, data science tools (Notebooks, R), ETL/analytics using Python, Java, or R

Preferred Skills & Certifications:

·        Databricks Certified Data Engineer Professional

·        2 years: deploying apps, gateways, agents, and models on Databricks

Scheduling:

·        Location: Onsite

·        Duration: 2 Months

·        Interview: In-Person