GCP Solutions Architect
Role details
Job location
Tech stack
Job description
As a Solution Architect on the Data Analytics Data Platform (DADP) team, you recommend, analyze, design, develop, and deliver business intelligence solutions primarily using Google Cloud Platform (GCP) data platform-related services. The Solution Architect is a proven professional using analytical and critical thinking skills with modern data platform solution development experience who creates scalable and reliable data solutions. The Architect is involved in all parts of the platform development process, from gathering requirements to solution delivery and documentation of lessons learned, along with recommending, designing & developing these client solutions. And as an NRI team member, you will provide top-notch service and suggestions not only to your clients and the project you're working on but also to your NRI teammates. Responsibilities
- Demonstrates passion, excellence, trust, transparency, and client focus.
- Partners with customers and stakeholders to architect data platform solutions that answer key business questions.
- Designs, proposes, builds, and maintains databases and data lakes, data pipelines that transform and model data, and reporting and analytics solutions.
- Understands business problems and processes based on direct conversations with customers, can see the big picture, and translate that into specific solutions.
- Efficiently, effectively, and carefully leverage and evaluate AI tools to develop data platforms and data analytics solutions.
- Is a trusted advisor in providing value and solutions to a variety of clients in different industries.
- Participates and contributes to internal Communities of Interest.
- Functions often as the technical lead on a project.
- Identifies issues early, proposes solutions, and tactfully raises concerns and proposes solutions.
- Builds data platform roadmaps and identifies milestones.
- Conducts code peer reviews.
- Clearly articulates pros and cons of various tools/approaches.
- Documents and diagrams proposed solutions.
- Orchestrates solutions to reduce data latency cost, picking the right service based on the workload.
- Uses Dataplex to unify data governance, cataloging, data quality, and lifecycle management across data lakes and data warehouses.
- Understands Google Cloud Platform (GCP) service pricing, plus how to monitor and manage costs as part of solution development.
- Approaches conflict directly, assumes positive intent, and seeks help from leaders if needed.
- Adapts positively to change by embracing new practices, processes, or circumstances.
- Presents a positive, professional, and self-confident image.
- Communicates accurately, concisely, and effectively.
- Respectfully listens to others' ideas and concerns with an open mind.
- Develops and maintains effective working relationships with others.
- Leads collaboratively to solve problems and puts team success first.
- Holds self and others accountable for responsibilities.
- Accepts responsibility for own decisions and actions without excuses.
- May balance multiple projects while still focusing on the needs of end users, clients, and the project manager.
Requirements
- 5-7 years of work experience in data engineering
- Your data engineering experience should include Google Cloud Platform (GCP) technologies and be deeply familiar with modern data platform technologies such as (at least two of these):
o BigQuery o Dataflow (Apache Beam) o Dataproc (managed Spark/Hadoop) o Cloud Composer (managed Apache Airflow) o Cloud Data Fusion o Looker / Looker Studio
- Adept at applying Agile engineering practices.
- Deep familiarity and experience in the following areas:
o Data warehouse and lake house methodologies including medallion architecture. o Data ETL/ELT processes o Data profiling and anomaly detection o Data modeling (Dimensional/Kimball) o SQL expertise o Python-skilled o Strong background in relational database platforms o DevOps/Continuous integration & continuous delivery
- Excellent understanding of data modeling options (e.g., OLTP vs OLAP, dimensional, data vault, slowly changing dimensions)
- Business analysis / data analysis skills
- Continual pursuit of further education and certifications
Preferred
- Bachelor's degree in Data Analytics, Computer Science, Information Systems, or a related field.
- Previous consulting experience
- Experience migrating data platforms and workloads from Microsoft Azure to Google Cloud Platform (GCP).
- Experience working with Informatica data cataloguing
- Google Cloud Professional Data Engineer certification (or equivalent GCP certification).
Competency Requirements
- Builds strong client relationships and delivery client centric solutions.
- Takes on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Holds self and others accountable to meet commitments.
- Builds partnerships and works collaboratively with others to meet shared objectives.
- Gains the confidence and trust of others through honesty, integrity, and authenticity.
- Develops and delivers multi-mode communications that convey a clear understanding of the unique needs of different audiences.